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CN114820951A - Wavelet and filter-based composite seabed geographic entity progressive decomposition method - Google Patents

Wavelet and filter-based composite seabed geographic entity progressive decomposition method Download PDF

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CN114820951A
CN114820951A CN202210732260.2A CN202210732260A CN114820951A CN 114820951 A CN114820951 A CN 114820951A CN 202210732260 A CN202210732260 A CN 202210732260A CN 114820951 A CN114820951 A CN 114820951A
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seabed
water depth
geographic
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geographic entity
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汪九尧
吴自银
赵荻能
周洁琼
朱超
王明伟
李家彪
李春峰
任建业
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Second Institute of Oceanography MNR
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Abstract

本发明公开了一种基于小波和滤波器的复合海底地理实体逐级分解方法，包括数据预处理、复合海底地理实体分离和特征提取三大步骤。首先，原始多波束水深数据通过预处理工作，完成地形地貌建模，构建得到水深模型；其次，将处理得到的水深模型，采用离散小波变换进行复合地形的逐级分解，确定分解级数，重构分离结果，从而分离出不同等级的海底地理实体；最后，通过海底地理实体界限确定和形态特征参数提取，构建海底地理实体的要素信息表。该方法将小波变换应用于海底地理实体的分解，有效解决了复杂海底地理实体难以界定、量化分析等难题。本发明可在海底地理实体划定、海洋测绘学、海洋工程建设等领域具有重要的实际应用价值。

Figure 202210732260

The invention discloses a step-by-step decomposition method for composite seabed geographic entities based on wavelets and filters, which includes three steps of data preprocessing, separation of composite seabed geographic entities and feature extraction. First, the original multi-beam bathymetry data is preprocessed to complete the topography and landform modeling, and a bathymetry model is constructed; secondly, the obtained bathymetry model is decomposed step by step using discrete wavelet transform, and the decomposition level is determined. The results of structure separation are used to separate different levels of seabed geographic entities. Finally, the element information table of seabed geographic entities is constructed through the determination of the boundaries of seabed geographic entities and the extraction of morphological characteristic parameters. This method applies wavelet transform to the decomposition of seabed geographic entities, which effectively solves the difficult problems of difficult definition and quantitative analysis of complex seabed geographic entities. The invention can have important practical application value in the fields of seabed geographic entity delineation, marine surveying and mapping, marine engineering construction and the like.

Figure 202210732260

Description

基于小波和滤波器的复合海底地理实体逐级分解方法A step-by-step decomposition method for composite seabed geographic entities based on wavelets and filters

技术领域technical field

本发明涉及海底地理实体划定、海洋测绘、海底地形地貌（不规则的表面或轮廓的计量）、海洋地质、海洋制图与图像数据处理、深海采矿和海洋工程建设等技术领域。The invention relates to the technical fields of seabed geographic entity delineation, marine surveying and mapping, seabed topography (measurement of irregular surface or contour), marine geology, marine mapping and image data processing, deep sea mining and marine engineering construction.

背景技术Background technique

海洋约占地球面积的71％，蕴藏丰富的人类赖以生存的资源。详细和精确的全球海底地形地貌信息将对我们认知、开发和利用海洋起到重要作用。然而，根据全球最大的海底地形测绘数据收集项目—“海底2030”的统计，目前只有约21%的全球海底已完成了地形地貌的高精度测绘，对海底地形的认知程度尚不及对火星、月球表面地形的认知。The ocean occupies about 71% of the earth's area and contains abundant resources for human survival. Detailed and precise global seafloor topography information will play an important role in our understanding, development and utilization of the ocean. However, according to the statistics of "Seabed 2030", the world's largest seabed topographic mapping data collection project, only about 21% of the global seabed has completed high-precision topographic mapping, and the understanding of seabed topography is not as good as that of Mars, Cognition of the topography of the lunar surface.

近半个世纪以来，在已掌握的高精度地形地貌信息的全球海底部分，人类通过将其划定为可测量、具有确定界线的地理实体，即海底地理实体，并依据相应的标准和规则，对这些地理实体进行识别、分类与命名。根据国际海底地名数据库统计，目前全球已完成4700多个海底地理实体的识别与命名工作。For nearly half a century, in the global seabed part of the high-precision topographic and geomorphological information that has been mastered, human beings have delineated it as a measurable and definite geographical entity with a definite boundary, that is, a seabed geographical entity, and according to corresponding standards and rules, Identify, classify, and name these geographic entities. According to statistics from the International Seabed Geographical Names Database, the identification and naming of more than 4,700 seabed geographic entities has been completed worldwide.

按照规模大小和主从关系，可以将海底地理实体可划分为多个级别。然而，尺度更小的次一级的海底地理实体往往叠加发育在尺度更大的上一级的海底地理实体上，产生一种形态异常复杂且包含多种级别实体的复合型海底地理实体。难以圈定、海底地理实体形态参数难以提取等问题，在开展实体划定前必须对其进行逐级分解，进而开展地理实体的量化研究。According to the scale and the master-slave relationship, the seabed geographic entities can be divided into multiple levels. However, the smaller-scale sub-level seabed geographic entities are often superimposed and developed on the larger-scale upper-level seabed geographic entities, resulting in a complex seafloor geographic entity that contains multiple levels of entities. It is difficult to delineate and extract the morphological parameters of seabed geographic entities. Before carrying out entity delineation, it must be decomposed step by step, and then carry out quantitative research on geographic entities.

针对多尺度地形分解的问题，国内外学者开展了一些相关研究。如Gutierrez等使用连续小波变换，结合鲁棒样条滤波器，对多种尺度的海底沙波进行了分解和分类，但是没有对分解后的各个尺度的沙波进行形态学方面的计算。同时，这种小尺度地形的分解方法难以直接应用到较大尺度的海底地理实体的逐级分解。For the problem of multi-scale terrain decomposition, domestic and foreign scholars have carried out some related research. For example, Gutierrez et al. used continuous wavelet transform, combined with robust spline filter, to decompose and classify seabed sand waves of various scales, but did not perform morphological calculations on the decomposed sand waves of various scales. At the same time, this small-scale terrain decomposition method is difficult to directly apply to the step-by-step decomposition of larger-scale seafloor geographic entities.

发明内容SUMMARY OF THE INVENTION

为了克服现有技术的不足，本发明的目的是提供一种基于小波和滤波器的复合海底地理实体逐级分解方法。In order to overcome the deficiencies of the prior art, the purpose of the present invention is to provide a step-by-step decomposition method for composite seabed geographic entities based on wavelets and filters.

本发明的目的通过以下技术方案实现：The object of the present invention is achieved through the following technical solutions:

一种基于小波和滤波器的复合海底地理实体逐级分解方法，包括数据预处理、复合海底地理实体分离和特征提取三大步骤：首先，数据预处理包括多波束水深数据预处理和地形地貌建模，构建得到水深模型；其次，复合海底地理实体分离包括采用离散小波变换进行复合地形的逐级分解、分解级数确定和分离结果重构，从而分离出不同等级的海底地理实体；最后，特征提取包括海底地理实体范围确定、形态特征参数提取和要素信息表构建。A step-by-step decomposition method for composite seabed geographic entities based on wavelets and filters, including three steps: data preprocessing, separation of composite seabed geographic entities, and feature extraction. secondly, the separation of complex seabed geographic entities includes the step-by-step decomposition of the composite terrain using discrete wavelet transform, the determination of the decomposition series and the reconstruction of the separation results, so as to separate different levels of seabed geographic entities; finally, the features The extraction includes determination of the range of seabed geographic entities, extraction of morphological feature parameters, and construction of element information tables.

所述的多波束水深数据预处理：对原始多波束水深数据进行CUBE滤波、声速改正、 异常值剔除处理，得到处理后的多波束水深数据集

Figure 837246DEST_PATH_IMAGE001
，其中x m 和y m 分别为全部多波束测深点的平面位置坐标值，
Figure 551124DEST_PATH_IMAGE002
为该多波束测深点的深度值，
Figure 642446DEST_PATH_IMAGE003
为 测深点数，
Figure 568814DEST_PATH_IMAGE004
和
Figure 179923DEST_PATH_IMAGE003
均为自然数。 The multi-beam bathymetry data preprocessing: CUBE filtering, sound velocity correction, and outlier elimination processing are performed on the original multi-beam bathymetry data to obtain a processed multi-beam bathymetry data set.
Figure 837246DEST_PATH_IMAGE001
, where x m and y m are the plane position coordinates of all multi-beam sounding points, respectively,
Figure 551124DEST_PATH_IMAGE002
is the depth value of the multi-beam sounding point,
Figure 642446DEST_PATH_IMAGE003
is the number of sounding points,
Figure 568814DEST_PATH_IMAGE004
and
Figure 179923DEST_PATH_IMAGE003
All are natural numbers.

所述的地形地貌建模：基于处理后的多波束水深数据集

Figure 284277DEST_PATH_IMAGE001
，采用样条函数内插法，构建得到原始水深模型
Figure 348048DEST_PATH_IMAGE005
，其中，X s,l 和Y s,l 分别为原始水深模型
Figure 78106DEST_PATH_IMAGE006
的第
Figure 792990DEST_PATH_IMAGE007
行、第
Figure 317513DEST_PATH_IMAGE008
列的平面位置坐标值，
Figure 603000DEST_PATH_IMAGE009
为原始水深模型
Figure 887482DEST_PATH_IMAGE006
中该 位置的深度值，
Figure 942026DEST_PATH_IMAGE010
和
Figure 168608DEST_PATH_IMAGE011
分别为该原始水深模型的总行数和总列数，
Figure 456239DEST_PATH_IMAGE007
、
Figure 262521DEST_PATH_IMAGE008
、
Figure 437150DEST_PATH_IMAGE010
和
Figure 569054DEST_PATH_IMAGE011
均为自然数。 Terrain modeling as described: based on processed multibeam bathymetry datasets
Figure 284277DEST_PATH_IMAGE001
, using the spline function interpolation method to construct the original water depth model
Figure 348048DEST_PATH_IMAGE005
, where X s,l and Y s,l are the original water depth models, respectively
Figure 78106DEST_PATH_IMAGE006
First
Figure 792990DEST_PATH_IMAGE007
row,
Figure 317513DEST_PATH_IMAGE008
the plane position coordinate value of the column,
Figure 603000DEST_PATH_IMAGE009
for the original bathymetric model
Figure 887482DEST_PATH_IMAGE006
the depth value at that location in ,
Figure 942026DEST_PATH_IMAGE010
and
Figure 168608DEST_PATH_IMAGE011
are the total number of rows and columns of the original water depth model, respectively,
Figure 456239DEST_PATH_IMAGE007
,
Figure 262521DEST_PATH_IMAGE008
,
Figure 437150DEST_PATH_IMAGE010
and
Figure 569054DEST_PATH_IMAGE011
All are natural numbers.

所述的采用离散小波变换进行复合地形的逐级分解：基于原始水深模型

Figure 579867DEST_PATH_IMAGE006
进行离散小波变换，通过Mallat算法与滤波器结合，实现小波多尺度分析， 将复合地形分解为低频的地形近似分量和高频的地形细节分量，每经过一次分解，近似分 量被分解为低一级的地形近似分量和地形细节分量，数据总量保持不变；分解算法表述为 公式：
Figure 455419DEST_PATH_IMAGE012
其中，
Figure 750134DEST_PATH_IMAGE013
为离散采样数据个 数，
Figure 325644DEST_PATH_IMAGE014
和
Figure 73021DEST_PATH_IMAGE015
分别为为分解过程采用的低通和高通滤波器系数，
Figure 486684DEST_PATH_IMAGE016
和
Figure 386638DEST_PATH_IMAGE017
分别为第
Figure 125924DEST_PATH_IMAGE018
级小 波分解得到的地形近似分量和地形细节分量。 The described step-by-step decomposition of composite terrain using discrete wavelet transform: based on the original water depth model
Figure 579867DEST_PATH_IMAGE006
Perform discrete wavelet transform, and combine the Mallat algorithm with filters to realize wavelet multi-scale analysis, and decompose the composite terrain into low-frequency terrain approximate components and high-frequency terrain detail components. After each decomposition, the approximate components are decomposed into a lower level. The terrain approximation component and terrain detail component of , the total amount of data remains unchanged; the decomposition algorithm is expressed as the formula:
Figure 455419DEST_PATH_IMAGE012
in,
Figure 750134DEST_PATH_IMAGE013
is the number of discrete sampling data,
Figure 325644DEST_PATH_IMAGE014
and
Figure 73021DEST_PATH_IMAGE015
are the low-pass and high-pass filter coefficients used for the decomposition process, respectively,
Figure 486684DEST_PATH_IMAGE016
and
Figure 386638DEST_PATH_IMAGE017
respectively
Figure 125924DEST_PATH_IMAGE018
The terrain approximation component and terrain detail component obtained by the wavelet decomposition.

所述的分解级数确定和分离结果重构：基于分解出的地形近似分量

Figure 95017DEST_PATH_IMAGE016
和地形 细节分量
Figure 561640DEST_PATH_IMAGE017
，依据频率分析信息，确定分解级数
Figure 565368DEST_PATH_IMAGE019
，并对分离结果进行 重构，重构式如下：
Figure 209976DEST_PATH_IMAGE020
，其中，
Figure 666365DEST_PATH_IMAGE021
和
Figure 438143DEST_PATH_IMAGE022
分 别为
Figure 30798DEST_PATH_IMAGE023
和
Figure 111887DEST_PATH_IMAGE024
的共轭，也即重列各滤波器组的系数，最终得到分离后的水深模型
Figure 570419DEST_PATH_IMAGE025
和
Figure 129576DEST_PATH_IMAGE026
，从而分离出不同等级的海底地理实体。 The described decomposition series determination and separation result reconstruction: based on the decomposed terrain approximation components
Figure 95017DEST_PATH_IMAGE016
and terrain detail components
Figure 561640DEST_PATH_IMAGE017
, according to the frequency analysis information, determine the decomposition level
Figure 565368DEST_PATH_IMAGE019
, and reconstruct the separation result, the reconstruction formula is as follows:
Figure 209976DEST_PATH_IMAGE020
,in,
Figure 666365DEST_PATH_IMAGE021
and
Figure 438143DEST_PATH_IMAGE022
respectively
Figure 30798DEST_PATH_IMAGE023
and
Figure 111887DEST_PATH_IMAGE024
The conjugate of , that is, the coefficients of each filter bank are rearranged, and finally the separated water depth model is obtained.
Figure 570419DEST_PATH_IMAGE025
and
Figure 129576DEST_PATH_IMAGE026
, so as to separate different levels of seabed geographic entities.

所述的海底地理实体范围确定：The scope of the said seabed geographic entity is determined:

（a）基于分离后的水深模型

Figure 107896DEST_PATH_IMAGE025
，按照海底地理实体的水深范围
Figure 579460DEST_PATH_IMAGE027
，确定海底地理实体范围
Figure 276021DEST_PATH_IMAGE028
，其中，
Figure 373290DEST_PATH_IMAGE029
和
Figure 252122DEST_PATH_IMAGE030
分别 为处于海底地理实体界限上的水深点的平面位置坐标值，
Figure 143854DEST_PATH_IMAGE031
为处于海底地理实体界限上的 水深点总数；基于海底地理实体范围
Figure 875181DEST_PATH_IMAGE032
对原始水深模型
Figure 822146DEST_PATH_IMAGE006
进行范围 截取并输出，得到截取后的水深模型
Figure 243900DEST_PATH_IMAGE033
， 其中，X s,l 和Y s,l 分别为截取后的水深模型
Figure 837693DEST_PATH_IMAGE034
的第
Figure 977687DEST_PATH_IMAGE007
行、第
Figure 698649DEST_PATH_IMAGE008
列的平面位置坐标 值，
Figure 506068DEST_PATH_IMAGE035
为截取后的水深模型
Figure 520030DEST_PATH_IMAGE034
中该平面位置的深度值，
Figure 412899DEST_PATH_IMAGE036
为截取后的 水深模型
Figure 921241DEST_PATH_IMAGE034
的最小水深，
Figure 68320DEST_PATH_IMAGE037
为截取后的水深模型
Figure 269494DEST_PATH_IMAGE034
的最大水深，
Figure 649660DEST_PATH_IMAGE010
和
Figure 210960DEST_PATH_IMAGE011
分别为截取后的水深模型
Figure 727392DEST_PATH_IMAGE034
的总行数和总列数，
Figure 568309DEST_PATH_IMAGE007
、
Figure 920924DEST_PATH_IMAGE008
、
Figure 771068DEST_PATH_IMAGE010
和
Figure 142007DEST_PATH_IMAGE011
均为自然数； (a) Based on the separated water depth model
Figure 107896DEST_PATH_IMAGE025
, according to the depth range of the seabed geographic entity
Figure 579460DEST_PATH_IMAGE027
, to determine the extent of seabed geographic entities
Figure 276021DEST_PATH_IMAGE028
,in,
Figure 373290DEST_PATH_IMAGE029
and
Figure 252122DEST_PATH_IMAGE030
are the coordinates of the plane position of the water depth point on the boundary of the seabed geographic entity, respectively,
Figure 143854DEST_PATH_IMAGE031
is the total number of bathymetric points that lie on the boundaries of the seabed geographic entity; based on the extent of the seabed geographic entity
Figure 875181DEST_PATH_IMAGE032
for the original bathymetric model
Figure 822146DEST_PATH_IMAGE006
Perform range interception and output to obtain the intercepted water depth model
Figure 243900DEST_PATH_IMAGE033
, where X s,l and Y s,l are the intercepted water depth models, respectively
Figure 837693DEST_PATH_IMAGE034
First
Figure 977687DEST_PATH_IMAGE007
row,
Figure 698649DEST_PATH_IMAGE008
the plane position coordinate value of the column,
Figure 506068DEST_PATH_IMAGE035
is the intercepted water depth model
Figure 520030DEST_PATH_IMAGE034
The depth value of the plane position in ,
Figure 412899DEST_PATH_IMAGE036
is the intercepted water depth model
Figure 921241DEST_PATH_IMAGE034
minimum water depth,
Figure 68320DEST_PATH_IMAGE037
is the intercepted water depth model
Figure 269494DEST_PATH_IMAGE034
the maximum water depth,
Figure 649660DEST_PATH_IMAGE010
and
Figure 210960DEST_PATH_IMAGE011
are the intercepted water depth models, respectively
Figure 727392DEST_PATH_IMAGE034
The total number of rows and total columns of ,
Figure 568309DEST_PATH_IMAGE007
,
Figure 920924DEST_PATH_IMAGE008
,
Figure 771068DEST_PATH_IMAGE010
and
Figure 142007DEST_PATH_IMAGE011
are all natural numbers;

（b）基于分离后的水深模型

Figure 403093DEST_PATH_IMAGE026
，求取其坡度模型
Figure 492271DEST_PATH_IMAGE038
，其中，X s,l 和Y s,l 分别为坡度模型
Figure 146107DEST_PATH_IMAGE039
的第
Figure 122284DEST_PATH_IMAGE007
行、第
Figure 570583DEST_PATH_IMAGE008
列的平面位置坐标值，
Figure 412637DEST_PATH_IMAGE040
为坡度模型
Figure 385010DEST_PATH_IMAGE039
中 该平面位置的坡度值；基于坡度模型
Figure 464961DEST_PATH_IMAGE039
，按照海底地理实体的坡度范围
Figure 100473DEST_PATH_IMAGE041
，确定海底地理实体范围
Figure 164244DEST_PATH_IMAGE042
，其中，
Figure 159882DEST_PATH_IMAGE043
和
Figure 343608DEST_PATH_IMAGE044
分别为处于海底地理实体界限上的坡度点的平面位置坐标值，
Figure 399288DEST_PATH_IMAGE045
为处于海底地理实体 界限上的坡度点总数；基于海底地理实体范围
Figure 950355DEST_PATH_IMAGE046
对原始水深模型
Figure 234837DEST_PATH_IMAGE006
进行范围截取并输出，得到截取后的水深模型
Figure 289381DEST_PATH_IMAGE047
，其中，X s,l 和Y s,l 分别为截 取后的水深模型
Figure 781542DEST_PATH_IMAGE048
的第
Figure 803594DEST_PATH_IMAGE007
行、第
Figure 875455DEST_PATH_IMAGE008
列的平面位置坐标值，
Figure 50084DEST_PATH_IMAGE035
为截取后 的水深模型
Figure 667142DEST_PATH_IMAGE048
中该平面位置的深度值，
Figure 927222DEST_PATH_IMAGE049
为截取后的水深模型
Figure 802774DEST_PATH_IMAGE048
的最小坡度，
Figure 831910DEST_PATH_IMAGE050
为截取后的水深模型
Figure 118403DEST_PATH_IMAGE048
的最大 坡度，
Figure 865779DEST_PATH_IMAGE010
和
Figure 545022DEST_PATH_IMAGE011
分别为截取后的水深模型
Figure 179397DEST_PATH_IMAGE048
的总行数和总列数，
Figure 653104DEST_PATH_IMAGE007
、
Figure 622197DEST_PATH_IMAGE008
、
Figure 573972DEST_PATH_IMAGE010
和
Figure 826968DEST_PATH_IMAGE011
均为自然数。 (b) Based on the separated water depth model
Figure 403093DEST_PATH_IMAGE026
, find its slope model
Figure 492271DEST_PATH_IMAGE038
, where X s,l and Y s,l are the slope models, respectively
Figure 146107DEST_PATH_IMAGE039
First
Figure 122284DEST_PATH_IMAGE007
row,
Figure 570583DEST_PATH_IMAGE008
the plane position coordinate value of the column,
Figure 412637DEST_PATH_IMAGE040
for the slope model
Figure 385010DEST_PATH_IMAGE039
Slope value at the location of this plane in ; based on the slope model
Figure 464961DEST_PATH_IMAGE039
, according to the slope extent of the seafloor geographic entity
Figure 100473DEST_PATH_IMAGE041
, to determine the extent of seabed geographic entities
Figure 164244DEST_PATH_IMAGE042
,in,
Figure 159882DEST_PATH_IMAGE043
and
Figure 343608DEST_PATH_IMAGE044
are the plane position coordinates of the slope point on the boundary of the seabed geographic entity, respectively,
Figure 399288DEST_PATH_IMAGE045
is the total number of slope points that lie on the boundaries of the seafloor geo-entity; based on the seafloor geo-entity extent
Figure 950355DEST_PATH_IMAGE046
for the original bathymetric model
Figure 234837DEST_PATH_IMAGE006
Perform range interception and output to obtain the intercepted water depth model
Figure 289381DEST_PATH_IMAGE047
, where X s,l and Y s,l are the intercepted water depth models, respectively
Figure 781542DEST_PATH_IMAGE048
First
Figure 803594DEST_PATH_IMAGE007
row,
Figure 875455DEST_PATH_IMAGE008
the plane position coordinate value of the column,
Figure 50084DEST_PATH_IMAGE035
is the intercepted water depth model
Figure 667142DEST_PATH_IMAGE048
The depth value of the plane position in ,
Figure 927222DEST_PATH_IMAGE049
is the intercepted water depth model
Figure 802774DEST_PATH_IMAGE048
the minimum slope of ,
Figure 831910DEST_PATH_IMAGE050
is the intercepted water depth model
Figure 118403DEST_PATH_IMAGE048
the maximum slope of ,
Figure 865779DEST_PATH_IMAGE010
and
Figure 545022DEST_PATH_IMAGE011
are the intercepted water depth models, respectively
Figure 179397DEST_PATH_IMAGE048
The total number of rows and total columns of ,
Figure 653104DEST_PATH_IMAGE007
,
Figure 622197DEST_PATH_IMAGE008
,
Figure 573972DEST_PATH_IMAGE010
and
Figure 826968DEST_PATH_IMAGE011
All are natural numbers.

所述的形态特征参数提取：基于截取后的水深模型

Figure 205997DEST_PATH_IMAGE051
，应用GIS软件 提取该海底地理实体的形态特征参数
Figure 662386DEST_PATH_IMAGE052
， 其中
Figure 417852DEST_PATH_IMAGE011
和
Figure 26819DEST_PATH_IMAGE053
分别代表该海底地理实体的长度和宽度，
Figure 107908DEST_PATH_IMAGE054
和
Figure 51593DEST_PATH_IMAGE036
分别代表该海底地 理实体的最大水深和最小水深，
Figure 345171DEST_PATH_IMAGE055
代表该海底地理实体的平均坡度，表示为局部地表坡 面的倾斜程度，当进行坡度计算时可表述为简化的差分公式：
Figure 307180DEST_PATH_IMAGE056
其中，
Figure 293590DEST_PATH_IMAGE057
，是x方向高程或水深变化率；
Figure 990151DEST_PATH_IMAGE058
，是y方向高程或水深变化率；基于该海底地理实体的形态特征参数
Figure 838152DEST_PATH_IMAGE059
判定该海底地理实体的等级
Figure 405400DEST_PATH_IMAGE060
和类型
Figure 93870DEST_PATH_IMAGE061
。 The morphological feature parameter extraction: based on the intercepted water depth model
Figure 205997DEST_PATH_IMAGE051
, using GIS software to extract the morphological characteristic parameters of the seabed geographic entity
Figure 662386DEST_PATH_IMAGE052
, in
Figure 417852DEST_PATH_IMAGE011
and
Figure 26819DEST_PATH_IMAGE053
represent the length and width of the seabed geographic entity, respectively,
Figure 107908DEST_PATH_IMAGE054
and
Figure 51593DEST_PATH_IMAGE036
represent the maximum and minimum water depths of the seabed geographic entity, respectively,
Figure 345171DEST_PATH_IMAGE055
Represents the average slope of the seabed geographic entity, expressed as the slope of the local surface slope, and can be expressed as a simplified difference formula when calculating the slope:
Figure 307180DEST_PATH_IMAGE056
in,
Figure 293590DEST_PATH_IMAGE057
, is the rate of change in the x -direction elevation or water depth;
Figure 990151DEST_PATH_IMAGE058
, is the y -direction elevation or water depth change rate; based on the morphological characteristic parameters of the seabed geographic entity
Figure 838152DEST_PATH_IMAGE059
Determining the class of the seabed geographic entity
Figure 405400DEST_PATH_IMAGE060
and type
Figure 93870DEST_PATH_IMAGE061
.

所述的要素信息表构建：基于海底地理实体范围

Figure 261415DEST_PATH_IMAGE062
、海底地理实体的形态特征 参数
Figure 896796DEST_PATH_IMAGE059
、海底地理实体的等级
Figure 849708DEST_PATH_IMAGE060
和类型
Figure 177922DEST_PATH_IMAGE061
，构建该海底地理实体的要 素信息表
Figure 803069DEST_PATH_IMAGE063
。 The described feature information table construction: based on the range of seabed geographic entities
Figure 261415DEST_PATH_IMAGE062
, morphological characteristic parameters of seabed geographic entities
Figure 896796DEST_PATH_IMAGE059
, the level of seabed geographic entities
Figure 849708DEST_PATH_IMAGE060
and type
Figure 177922DEST_PATH_IMAGE061
, construct the feature information table of the seabed geographic entity
Figure 803069DEST_PATH_IMAGE063
.

本发明有益效果是：The beneficial effects of the present invention are:

本发明基于实测多波束水深数据，提供了一种针对复合海底地理实体的分解方法，采用离散小波变换进行复合地形的逐级分解，将复合型海底地理实体分解成不同等级的地貌单元，解决了复杂海底地理实体难以界定、量化分析等难题。Based on the measured multi-beam water depth data, the present invention provides a decomposition method for composite seabed geographic entities. The discrete wavelet transform is used to perform the step-by-step decomposition of the composite terrain, and the composite seabed geographic entities are decomposed into different levels of landform units. It is difficult to define and quantitatively analyze complex seabed geographic entities.

本发明可在海底地理实体划定、海洋测绘学、海底工程建设等方面具有重要的实际应用价值。The invention can have important practical application value in delineation of seabed geographical entities, marine surveying and mapping, seabed engineering construction and the like.

附图说明Description of drawings

图1是本发明的基于小波和滤波器的复合海底地理实体逐级分解方法的一种流程图。FIG. 1 is a flow chart of a method for decomposing a composite seabed geographic entity step by step based on a wavelet and a filter of the present invention.

图2是原始水深模型。Figure 2 is the original water depth model.

图3是一级海底地理实体分离结果图。Figure 3 is a diagram of the separation results of the first-level seabed geographic entities.

图4是二级海底地理实体分离结果图。Figure 4 is a diagram of the separation results of secondary seabed geographic entities.

图5是经过水深范围截取后的海底地理实体的水深模型。Fig. 5 is the water depth model of the seabed geographic entity after the interception of the water depth range.

图6是经过坡度范围截取后的海底地理实体的水深模型。Fig. 6 is a water depth model of the seabed geographic entity intercepted by the slope range.

具体实施方式Detailed ways

下面结合实例和附图对本发明作具体阐述。The present invention will be described in detail below with reference to examples and accompanying drawings.

实施例1典型陆坡地形为例的具体应用Example 1 Specific application of typical land slope terrain as an example

如附图1所示，本实例描述的是基于小波和滤波器的复合海底地理实体逐级分解方法，包括数据预处理、复合海底地理实体分离和特征提取三大步骤。As shown in FIG. 1 , this example describes a method for decomposing composite seabed geographical entities step by step based on wavelets and filters, including three steps of data preprocessing, separation of composite seabed geographical entities and feature extraction.

首先，数据预处理包括多波束水深数据预处理和地形地貌建模，构建得到水深模型；其次，复合海底地理实体分离包括采用离散小波变换进行复合地形的逐级分解、分解级数确定和分离结果重构，从而分离出不同等级的海底地理实体；最后，特征提取包括海底地理实体范围确定、形态特征参数提取和要素信息表构建。First, data preprocessing includes multi-beam bathymetry data preprocessing and topographic modeling, and a bathymetric model is constructed; secondly, the separation of composite seabed geographic entities includes the step-by-step decomposition of composite terrain using discrete wavelet transform, the determination of decomposition levels, and the separation results Reconstruction to separate different levels of seabed geographic entities; finally, feature extraction includes the determination of the scope of seabed geographic entities, the extraction of morphological feature parameters, and the construction of element information tables.

数据预处理包括多波束水深数据预处理和地形地貌建模，构建得到水深模型，图2展示了基于258万个测深点原始多波束测深数据利用样条函数内插法建模得到包含386行、470列的原始水深模型，具体步骤包括：Data preprocessing includes multi-beam bathymetry data preprocessing and topography modeling, and a bathymetric model is constructed. Figure 2 shows the original multi-beam bathymetry data based on 2.58 million sounding points. The original water depth model with 470 rows and 470 columns, the specific steps include:

（i）多波束水深数据预处理：(i) Multi-beam bathymetry data preprocessing:

对原始多波束水深数据进行CUBE滤波、声速改正、异常值剔除处理，得到处理后的 多波束水深数据集

Figure 773299DEST_PATH_IMAGE064
，其中 xm和ym分别为全部多波 束测深点的平面位置坐标值，
Figure 315139DEST_PATH_IMAGE002
为该多波束测深点的深度值。 Perform CUBE filtering, sound velocity correction, and outlier removal processing on the original multi-beam bathymetry data to obtain the processed multi-beam bathymetry data set
Figure 773299DEST_PATH_IMAGE064
, where x m and y m are the plane position coordinates of all multi-beam sounding points, respectively,
Figure 315139DEST_PATH_IMAGE002
is the depth value of the multi-beam sounding point.

（ii）地形地貌建模：(ii) Terrain modeling:

基于处理后的多波束水深数据集

Figure 814253DEST_PATH_IMAGE064
，采用样 条函数内插法，构建得到原始水深模型
Figure 690811DEST_PATH_IMAGE065
， 其中X s,l 和Y s,l 分别为原始水深模型
Figure 667995DEST_PATH_IMAGE006
的第
Figure 329920DEST_PATH_IMAGE007
行、第
Figure 999936DEST_PATH_IMAGE008
列的平面位置坐标值，
Figure 865255DEST_PATH_IMAGE009
为原始水深模型
Figure 646129DEST_PATH_IMAGE006
中该位置的深度值，该原始水深模型的总行数
Figure 428140DEST_PATH_IMAGE010
为 386行和总列数
Figure 541762DEST_PATH_IMAGE011
为470列，构建得到的原始水深模型见图2。 Based on processed multi-beam bathymetry dataset
Figure 814253DEST_PATH_IMAGE064
, using the spline function interpolation method to construct the original water depth model
Figure 690811DEST_PATH_IMAGE065
, where X s,l and Y s,l are the original water depth model, respectively
Figure 667995DEST_PATH_IMAGE006
First
Figure 329920DEST_PATH_IMAGE007
row,
Figure 999936DEST_PATH_IMAGE008
the plane position coordinate value of the column,
Figure 865255DEST_PATH_IMAGE009
for the original bathymetric model
Figure 646129DEST_PATH_IMAGE006
The depth value at this location in the total number of rows of the original bathymetry model
Figure 428140DEST_PATH_IMAGE010
for 386 rows and total columns
Figure 541762DEST_PATH_IMAGE011
For 470 columns, the constructed original water depth model is shown in Figure 2.

复合海底地理实体分离包括采用离散小波变换进行复合地形的逐级分解、分解级数确定和分离结果重构，从而分离出不同等级的海底地理实体，图3和图4展示了复合海底地理实体的分离结果，分别为一级海底地理实体：大陆坡；二级海底地理实体：海山、海丘和海底峡谷，具体步骤包括：The separation of composite seabed geographic entities includes the step-by-step decomposition of the composite terrain by discrete wavelet transform, the determination of the decomposition level and the reconstruction of the separation results, so as to separate different levels of seabed geographic entities. Figures 3 and 4 show the composite seabed geographic entities The separation results are as follows: first-level seabed geographic entities: continental slope; second-level seabed geographic entities: seamounts, sea mounds and submarine canyons. The specific steps include:

（i）采用离散小波变换进行复合地形的逐级分解:(i) Step-by-step decomposition of composite terrain using discrete wavelet transform:

基于原始水深模型

Figure 409224DEST_PATH_IMAGE065
进行离散 小波变换，通过Mallat算法与滤波器结合，实现小波多尺度分析，将复合地形分解为低频的 地形近似分量和高频的地形细节分量，每经过一次分解，近似分量被分解为低一级的地形 近似分量和地形细节分量，数据总量保持不变。分解算法表述为公式：
Figure 993789DEST_PATH_IMAGE012
其中，
Figure 364728DEST_PATH_IMAGE013
为离散采样数据个数，
Figure 392858DEST_PATH_IMAGE014
和
Figure 216457DEST_PATH_IMAGE015
分别为分解过程采用的低通和高通滤波器系数，
Figure 870293DEST_PATH_IMAGE016
和
Figure 876164DEST_PATH_IMAGE017
分别为第
Figure 324463DEST_PATH_IMAGE018
级小波分解 得到的地形近似分量和地形细节分量。 Based on original water depth model
Figure 409224DEST_PATH_IMAGE065
The discrete wavelet transform is performed, and the Mallat algorithm is combined with the filter to realize multi-scale wavelet analysis, and the composite terrain is decomposed into low-frequency terrain approximate components and high-frequency terrain detail components. After each decomposition, the approximate components are decomposed into a lower level The terrain approximation component and terrain detail component of , the total amount of data remains the same. The decomposition algorithm is expressed as the formula:
Figure 993789DEST_PATH_IMAGE012
in,
Figure 364728DEST_PATH_IMAGE013
is the number of discrete sampling data,
Figure 392858DEST_PATH_IMAGE014
and
Figure 216457DEST_PATH_IMAGE015
are the low-pass and high-pass filter coefficients used in the decomposition process, respectively,
Figure 870293DEST_PATH_IMAGE016
and
Figure 876164DEST_PATH_IMAGE017
respectively
Figure 324463DEST_PATH_IMAGE018
The terrain approximation component and terrain detail component obtained by the wavelet decomposition.

（ii）分解级数确定和分离结果重构：(ii) Decomposition series determination and separation result reconstruction:

基于分解出的地形近似分量

Figure 651670DEST_PATH_IMAGE016
和地形细节分量
Figure 843617DEST_PATH_IMAGE017
，依据频率分析信息，确 定分解级数
Figure 923568DEST_PATH_IMAGE019
为6级，并对分离结果进行重构，分离结果重构是分解算法 的逆过程，其原理就是利用地形近似分量
Figure 542768DEST_PATH_IMAGE016
和地形细节分量
Figure 855807DEST_PATH_IMAGE017
复原分离结果，重构 式如下：
Figure 585865DEST_PATH_IMAGE020
，其中，
Figure 785903DEST_PATH_IMAGE021
和
Figure 326737DEST_PATH_IMAGE022
分别为
Figure 612224DEST_PATH_IMAGE023
和
Figure 880395DEST_PATH_IMAGE024
的共轭，也即重列各滤波器组的系数，最终得到分离后的水深模型
Figure 934938DEST_PATH_IMAGE025
和
Figure 879629DEST_PATH_IMAGE026
，从而分离出不同等级的海底地理实体。 Based on the decomposed terrain approximation components
Figure 651670DEST_PATH_IMAGE016
and terrain detail components
Figure 843617DEST_PATH_IMAGE017
, according to the frequency analysis information, determine the decomposition level
Figure 923568DEST_PATH_IMAGE019
It is level 6, and the separation result is reconstructed. The reconstruction of the separation result is the inverse process of the decomposition algorithm. The principle is to use the terrain approximation component.
Figure 542768DEST_PATH_IMAGE016
and terrain detail components
Figure 855807DEST_PATH_IMAGE017
To restore the separation result, the reconstruction formula is as follows:
Figure 585865DEST_PATH_IMAGE020
,in,
Figure 785903DEST_PATH_IMAGE021
and
Figure 326737DEST_PATH_IMAGE022
respectively
Figure 612224DEST_PATH_IMAGE023
and
Figure 880395DEST_PATH_IMAGE024
The conjugate of , that is, the coefficients of each filter bank are rearranged, and finally the separated water depth model is obtained.
Figure 934938DEST_PATH_IMAGE025
and
Figure 879629DEST_PATH_IMAGE026
, so as to separate different levels of seabed geographic entities.

特征提取包括海底地理实体范围确定、形态特征参数提取和要素信息表构建，图5展示了经过水深范围截取后的海底地理实体的水深模型，附表1展示了该海底地理实体的要素信息表，具体步骤包括：Feature extraction includes determination of the scope of seabed geographic entities, extraction of morphological feature parameters, and construction of element information tables. Figure 5 shows the water depth model of the seabed geographic entities after the interception of the water depth range. Attached Table 1 shows the element information table of the seabed geographic entities. Specific steps include:

（i）海底地理实体范围确定：(i) Determination of the extent of seabed geographic entities:

基于分离后的水深模型

Figure 652413DEST_PATH_IMAGE025
，确定海底地理实体水深范围为[200 m， 3600 m]，确定海底地理实体范围
Figure 989854DEST_PATH_IMAGE066
，其中，
Figure 649636DEST_PATH_IMAGE029
和
Figure 781541DEST_PATH_IMAGE030
分别为处于海底地理实体界限上的水深点的平面位置坐标值，
Figure 776041DEST_PATH_IMAGE031
为处于海底地理 实体界限上的水深点总数； Based on the separated water depth model
Figure 652413DEST_PATH_IMAGE025
, determine the depth range of the seabed geographic entity as [200 m, 3600 m], and determine the scope of the seabed geographic entity
Figure 989854DEST_PATH_IMAGE066
,in,
Figure 649636DEST_PATH_IMAGE029
and
Figure 781541DEST_PATH_IMAGE030
are the coordinates of the plane position of the water depth point on the boundary of the seabed geographic entity, respectively,
Figure 776041DEST_PATH_IMAGE031
is the total number of bathymetric points that lie on the boundaries of the geographical entity of the seabed;

基于海底地理实体范围

Figure 651593DEST_PATH_IMAGE067
对原始水深模型
Figure 195576DEST_PATH_IMAGE006
进 行范围截取并输出，得到截取后的水深模型
Figure 232802DEST_PATH_IMAGE068
，其中，X s,l 和Y s,l 分别为截 取后的水深模型
Figure 980178DEST_PATH_IMAGE069
的第
Figure 393842DEST_PATH_IMAGE007
行、第
Figure 28217DEST_PATH_IMAGE008
列的平面位置坐标值，
Figure 236344DEST_PATH_IMAGE035
为截取后 的水深模型
Figure 205437DEST_PATH_IMAGE069
中该平面位置的深度值，截取后的水深模型见图5。 Based on the extent of seabed geographic entities
Figure 651593DEST_PATH_IMAGE067
for the original bathymetric model
Figure 195576DEST_PATH_IMAGE006
Perform range interception and output to obtain the intercepted water depth model
Figure 232802DEST_PATH_IMAGE068
, where X s,l and Y s,l are the intercepted water depth models, respectively
Figure 980178DEST_PATH_IMAGE069
First
Figure 393842DEST_PATH_IMAGE007
row,
Figure 28217DEST_PATH_IMAGE008
the plane position coordinate value of the column,
Figure 236344DEST_PATH_IMAGE035
is the intercepted water depth model
Figure 205437DEST_PATH_IMAGE069
The depth value of the plane position in the middle, the water depth model after interception is shown in Figure 5.

(ii)形态特征参数提取：(ii) Extraction of morphological feature parameters:

基于截取后的水深模型

Figure 422792DEST_PATH_IMAGE069
应用GIS软件提取该海底地理实体 的形态特征参数
Figure 410209DEST_PATH_IMAGE052
，其中
Figure 54817DEST_PATH_IMAGE011
和
Figure 776785DEST_PATH_IMAGE053
分别 代表该海底地理实体的长度和宽度，
Figure 282984DEST_PATH_IMAGE054
和
Figure 141218DEST_PATH_IMAGE036
分别代表该海底地理实体的最大水深和 最小水深，
Figure 956728DEST_PATH_IMAGE055
代表该海底地理实体的平均坡度，表示为局部地表坡面的倾斜程度，当进行 坡度计算时可表述为简化的差分公式：
Figure 634834DEST_PATH_IMAGE056
其中，
Figure 443259DEST_PATH_IMAGE057
，是x方向高程或水深变化率；
Figure 156000DEST_PATH_IMAGE058
，是y方向高程或水深变化率；得 到该海底地理实体长度
Figure 142410DEST_PATH_IMAGE070
=527 km，宽度
Figure 573391DEST_PATH_IMAGE071
=271 km，最大水深
Figure 686972DEST_PATH_IMAGE072
= 3600 m，最小水深
Figure 254220DEST_PATH_IMAGE036
= 200 m，平均坡度
Figure 411532DEST_PATH_IMAGE055
= 0.65°。 Based on the intercepted water depth model
Figure 422792DEST_PATH_IMAGE069
Using GIS software to extract the morphological characteristic parameters of the seabed geographic entity
Figure 410209DEST_PATH_IMAGE052
,in
Figure 54817DEST_PATH_IMAGE011
and
Figure 776785DEST_PATH_IMAGE053
represent the length and width of the seabed geographic entity, respectively,
Figure 282984DEST_PATH_IMAGE054
and
Figure 141218DEST_PATH_IMAGE036
represent the maximum and minimum water depths of the seabed geographic entity, respectively,
Figure 956728DEST_PATH_IMAGE055
Represents the average slope of the seabed geographic entity, expressed as the slope of the local surface slope, and can be expressed as a simplified difference formula when calculating the slope:
Figure 634834DEST_PATH_IMAGE056
in,
Figure 443259DEST_PATH_IMAGE057
, is the rate of change in the x -direction elevation or water depth;
Figure 156000DEST_PATH_IMAGE058
, is the rate of change of elevation or water depth in the y direction; get the length of the seabed geographic entity
Figure 142410DEST_PATH_IMAGE070
=527 km, width
Figure 573391DEST_PATH_IMAGE071
=271 km, maximum water depth
Figure 686972DEST_PATH_IMAGE072
= 3600 m, minimum water depth
Figure 254220DEST_PATH_IMAGE036
= 200 m, average slope
Figure 411532DEST_PATH_IMAGE055
= 0.65°.

基于该海底地理实体的形态特征参数

Figure 64230DEST_PATH_IMAGE059
判定该海底地理实体的等级
Figure 214457DEST_PATH_IMAGE060
为一级和类型
Figure 901791DEST_PATH_IMAGE061
为大陆坡。 Based on the morphological characteristic parameters of the seabed geographic entity
Figure 64230DEST_PATH_IMAGE059
Determining the class of the seabed geographic entity
Figure 214457DEST_PATH_IMAGE060
for level and type
Figure 901791DEST_PATH_IMAGE061
for the continental slope.

(iii)要素信息表构建：(iii) Construction of element information table:

基于海底地理实体范围

Figure 230004DEST_PATH_IMAGE062
、海底地理实体的形态特征参数
Figure 369998DEST_PATH_IMAGE059
、海 底地理实体的等级
Figure 559802DEST_PATH_IMAGE060
和类型
Figure 101642DEST_PATH_IMAGE061
，构建该海底地理实体的要素信息表Manifest= {Grade，Type，Area，Parameters}={一级，大陆坡，[200，3600]，km，km，3600m，200m，0.65°}， 构建得到的海底地理实体的要素信息表见下表1： Based on the extent of seabed geographic entities
Figure 230004DEST_PATH_IMAGE062
, morphological characteristic parameters of seabed geographic entities
Figure 369998DEST_PATH_IMAGE059
, the level of seabed geographic entities
Figure 559802DEST_PATH_IMAGE060
and type
Figure 101642DEST_PATH_IMAGE061
, construct the element information table Manifest= {Grade, Type, Area, Parameters} = {first class, continental slope, [200, 3600], km, km, 3600m, 200m, 0.65°}, constructed The element information table of seabed geographic entities is shown in Table 1 below:

Figure DEST_PATH_IMAGE073
Figure DEST_PATH_IMAGE073

实施例2 以典型海山地形为例的具体应用Example 2 Specific application of typical seamount topography as an example

如图1所示，本实例描述的是基于小波和滤波器的复合海底地理实体逐级分解方法，包括数据预处理、复合海底地理实体分离和特征提取三大步骤。As shown in Figure 1, this example describes a step-by-step decomposition method of composite seabed geographic entities based on wavelets and filters, including three steps: data preprocessing, separation of composite seabed geographic entities, and feature extraction.

首先，数据预处理包括多波束水深数据预处理和地形地貌建模，构建得到水深模型；其次，复合海底地理实体分离包括采用离散小波变换进行复合地形的逐级分解、分解级数确定和分离结果重构，从而分离出不同等级的海底地理实体；最后，特征提取包括海底地理实体范围确定、形态特征参数提取和要素信息表构建。First, data preprocessing includes multi-beam bathymetry data preprocessing and topographic modeling, and a bathymetric model is constructed; secondly, the separation of composite seabed geographic entities includes the step-by-step decomposition of composite terrain using discrete wavelet transform, the determination of decomposition levels, and the separation results Reconstruction to separate different levels of seabed geographic entities; finally, feature extraction includes the determination of the scope of seabed geographic entities, the extraction of morphological feature parameters, and the construction of element information tables.

数据预处理包括多波束水深数据预处理和地形地貌建模，构建得到水深模型，图2展示了基于258万个测深点原始多波束测深数据利用样条函数内插法建模得到包含386行、470列的原始水深模型，具体步骤包括：Data preprocessing includes multi-beam bathymetry data preprocessing and topography modeling, and a bathymetric model is constructed. Figure 2 shows the original multi-beam bathymetry data based on 2.58 million sounding points. The original water depth model with 470 rows and 470 columns, the specific steps include:

（i）多波束水深数据预处理：(i) Multi-beam bathymetry data preprocessing:

对原始多波束水深数据进行CUBE滤波、声速改正、异常值剔除处理，得到处理后的 多波束水深数据集

Figure 912341DEST_PATH_IMAGE064
，其中xm和ym分别为全部多波 束测深点的平面位置坐标值，
Figure 539631DEST_PATH_IMAGE002
为该多波束测深点的深度值。 Perform CUBE filtering, sound velocity correction, and outlier removal processing on the original multi-beam bathymetry data to obtain the processed multi-beam bathymetry data set
Figure 912341DEST_PATH_IMAGE064
, where x m and y m are the plane position coordinates of all multi-beam sounding points, respectively,
Figure 539631DEST_PATH_IMAGE002
is the depth value of the multi-beam sounding point.

（ii）地形地貌建模：(ii) Terrain modeling:

基于处理后的多波束水深数据集

Figure 782394DEST_PATH_IMAGE064
，采用样 条函数内插法，构建得到原始水深模型
Figure 444319DEST_PATH_IMAGE065
， 其中X s,l 和Y s,l 分别为原始水深模型
Figure 865067DEST_PATH_IMAGE006
的第
Figure 714075DEST_PATH_IMAGE007
行、第
Figure 760528DEST_PATH_IMAGE008
列的平面位置坐标值，
Figure 276960DEST_PATH_IMAGE009
为原始水深模型
Figure 367145DEST_PATH_IMAGE006
中该位置的深度值，该原始水深模型的总行数
Figure 703448DEST_PATH_IMAGE010
为 386行和总列数
Figure 288013DEST_PATH_IMAGE011
为470列，构建得到的原始水深模型见图2。 Based on processed multi-beam bathymetry dataset
Figure 782394DEST_PATH_IMAGE064
, using the spline function interpolation method to construct the original water depth model
Figure 444319DEST_PATH_IMAGE065
, where X s,l and Y s,l are the original water depth model, respectively
Figure 865067DEST_PATH_IMAGE006
First
Figure 714075DEST_PATH_IMAGE007
row,
Figure 760528DEST_PATH_IMAGE008
the plane position coordinate value of the column,
Figure 276960DEST_PATH_IMAGE009
for the original bathymetric model
Figure 367145DEST_PATH_IMAGE006
The depth value at this location in the total number of rows of the original bathymetry model
Figure 703448DEST_PATH_IMAGE010
for 386 rows and total columns
Figure 288013DEST_PATH_IMAGE011
For 470 columns, the constructed original water depth model is shown in Figure 2.

复合海底地理实体分离包括采用离散小波变换进行复合地形的逐级分解、分解级数确定和分离结果重构，从而分离出不同等级的海底地理实体，图3和图4展示了复合海底地理实体的分离结果，分别为一级海底地理实体：大陆坡；二级海底地理实体：海山、海丘和海底峡谷，具体步骤包括：The separation of composite seabed geographic entities includes the step-by-step decomposition of the composite terrain by discrete wavelet transform, the determination of the decomposition level and the reconstruction of the separation results, so as to separate different levels of seabed geographic entities. Figures 3 and 4 show the composite seabed geographic entities The separation results are as follows: first-level seabed geographic entities: continental slope; second-level seabed geographic entities: seamounts, sea mounds and submarine canyons. The specific steps include:

（i）采用离散小波变换进行复合地形的逐级分解:(i) Step-by-step decomposition of composite terrain using discrete wavelet transform:

基于原始水深模型

Figure 658952DEST_PATH_IMAGE065
进行离散 小波变换，通过Mallat算法与滤波器结合，实现小波多尺度分析，将复合地形分解为低频的 地形近似分量和高频的地形细节分量，每经过一次分解，近似分量被分解为低一级的地形 近似分量和地形细节分量，数据总量保持不变。分解算法表述为公式：
Figure 421502DEST_PATH_IMAGE012
其中，
Figure 510681DEST_PATH_IMAGE013
为离散采样数据个数，
Figure 633358DEST_PATH_IMAGE014
和
Figure 124382DEST_PATH_IMAGE015
分别为分解过程采用的低通和高通滤波器系数，
Figure 556369DEST_PATH_IMAGE016
和
Figure 867265DEST_PATH_IMAGE017
分别为第
Figure 793633DEST_PATH_IMAGE018
级小波分解得 到的地形近似分量和地形细节分量。 Based on original water depth model
Figure 658952DEST_PATH_IMAGE065
The discrete wavelet transform is performed, and the Mallat algorithm is combined with the filter to realize multi-scale wavelet analysis, and the composite terrain is decomposed into low-frequency terrain approximate components and high-frequency terrain detail components. After each decomposition, the approximate components are decomposed into a lower level The terrain approximation component and terrain detail component of , the total amount of data remains the same. The decomposition algorithm is expressed as the formula:
Figure 421502DEST_PATH_IMAGE012
in,
Figure 510681DEST_PATH_IMAGE013
is the number of discrete sampling data,
Figure 633358DEST_PATH_IMAGE014
and
Figure 124382DEST_PATH_IMAGE015
are the low-pass and high-pass filter coefficients used in the decomposition process, respectively,
Figure 556369DEST_PATH_IMAGE016
and
Figure 867265DEST_PATH_IMAGE017
respectively
Figure 793633DEST_PATH_IMAGE018
The terrain approximation component and terrain detail component obtained by the wavelet decomposition.

ii）分解级数确定和分离结果重构：ii) Decomposition series determination and separation result reconstruction:

基于分解出的地形近似分量

Figure 139163DEST_PATH_IMAGE016
和地形细节分量
Figure 243517DEST_PATH_IMAGE017
，依据频率分析信息，确 定分解级数
Figure 41709DEST_PATH_IMAGE019
为6级，并对分离结果进行重构，分离结果重构是分解算法 的逆过程，其原理就是利用地形近似分量
Figure 37346DEST_PATH_IMAGE016
和地形细节分量
Figure 971804DEST_PATH_IMAGE017
复原分离结果，重构 式如下：
Figure 745594DEST_PATH_IMAGE020
，其中，
Figure 296661DEST_PATH_IMAGE021
和
Figure 830411DEST_PATH_IMAGE022
分别为
Figure 635687DEST_PATH_IMAGE023
和
Figure 331110DEST_PATH_IMAGE024
的共轭，也即重列各滤波器组的系数，最终得到分离后的水深模型
Figure 103894DEST_PATH_IMAGE025
和
Figure 175756DEST_PATH_IMAGE026
，从而分离出不同等级的海底地理实体。 Based on the decomposed terrain approximation components
Figure 139163DEST_PATH_IMAGE016
and terrain detail components
Figure 243517DEST_PATH_IMAGE017
, according to the frequency analysis information, determine the decomposition level
Figure 41709DEST_PATH_IMAGE019
It is level 6, and the separation result is reconstructed. The reconstruction of the separation result is the inverse process of the decomposition algorithm. The principle is to use the terrain approximation component.
Figure 37346DEST_PATH_IMAGE016
and terrain detail components
Figure 971804DEST_PATH_IMAGE017
To restore the separation result, the reconstruction formula is as follows:
Figure 745594DEST_PATH_IMAGE020
,in,
Figure 296661DEST_PATH_IMAGE021
and
Figure 830411DEST_PATH_IMAGE022
respectively
Figure 635687DEST_PATH_IMAGE023
and
Figure 331110DEST_PATH_IMAGE024
The conjugate of , that is, the coefficients of each filter bank are rearranged, and finally the separated water depth model is obtained.
Figure 103894DEST_PATH_IMAGE025
and
Figure 175756DEST_PATH_IMAGE026
, so as to separate different levels of seabed geographic entities.

分离结果重构是分解算法的逆过程，其原理就是利用地形近似分量

Figure 334073DEST_PATH_IMAGE016
和地形 细节分量
Figure 465977DEST_PATH_IMAGE017
复原分离结果，重构式如下：
Figure 460478DEST_PATH_IMAGE020
， 其中，
Figure 336030DEST_PATH_IMAGE021
和
Figure 850319DEST_PATH_IMAGE022
分别为
Figure 153125DEST_PATH_IMAGE023
和
Figure 634922DEST_PATH_IMAGE024
的共轭，也即重列各滤波器组的系数。 The reconstruction of the separation result is the inverse process of the decomposition algorithm, and its principle is to use the terrain approximation components
Figure 334073DEST_PATH_IMAGE016
and terrain detail components
Figure 465977DEST_PATH_IMAGE017
To restore the separation result, the reconstruction formula is as follows:
Figure 460478DEST_PATH_IMAGE020
, in,
Figure 336030DEST_PATH_IMAGE021
and
Figure 850319DEST_PATH_IMAGE022
respectively
Figure 153125DEST_PATH_IMAGE023
and
Figure 634922DEST_PATH_IMAGE024
The conjugate of , that is, the coefficients of each filter bank are rearranged.

特征提取包括海底地理实体范围确定、形态特征参数提取和要素信息表构建，图6展示了经过坡度范围截取后的海底地理实体的水深模型，，具体步骤包括：Feature extraction includes determination of the range of seabed geographic entities, extraction of morphological feature parameters, and construction of element information tables. Figure 6 shows the water depth model of seabed geographic entities after interception by the slope range. The specific steps include:

（i）海底地理实体范围确定：(i) Determination of the extent of seabed geographic entities:

基于分离后的水深模型

Figure 48585DEST_PATH_IMAGE026
，求取其坡度模型
Figure 181495DEST_PATH_IMAGE074
，其中，X s,l 和Y s,l 分别为坡度模型
Figure 655202DEST_PATH_IMAGE039
的第
Figure 624295DEST_PATH_IMAGE007
行、第
Figure 841650DEST_PATH_IMAGE008
列的平面位置坐标值，
Figure 330531DEST_PATH_IMAGE040
为坡度模型
Figure 975139DEST_PATH_IMAGE039
中该平面位置的坡度值。 Based on the separated water depth model
Figure 48585DEST_PATH_IMAGE026
, find its slope model
Figure 181495DEST_PATH_IMAGE074
, where X s,l and Y s,l are the slope models, respectively
Figure 655202DEST_PATH_IMAGE039
First
Figure 624295DEST_PATH_IMAGE007
row,
Figure 841650DEST_PATH_IMAGE008
the plane position coordinate value of the column,
Figure 330531DEST_PATH_IMAGE040
for the slope model
Figure 975139DEST_PATH_IMAGE039
The slope value at the location of this plane in .

基于坡度模型

Figure 431528DEST_PATH_IMAGE039
，按照海底地理实体的坡度范围
Figure 186995DEST_PATH_IMAGE075
，确 定海底地理实体范围
Figure 91234DEST_PATH_IMAGE076
，其中，
Figure 641164DEST_PATH_IMAGE043
和
Figure 584850DEST_PATH_IMAGE044
分别为处于 海底地理实体界限上的坡度点的平面位置坐标值，
Figure 894739DEST_PATH_IMAGE045
为处于海底地理实体界限上的坡度点 总数。 Slope based model
Figure 431528DEST_PATH_IMAGE039
, according to the slope extent of the seafloor geographic entity
Figure 186995DEST_PATH_IMAGE075
, to determine the extent of seabed geographic entities
Figure 91234DEST_PATH_IMAGE076
,in,
Figure 641164DEST_PATH_IMAGE043
and
Figure 584850DEST_PATH_IMAGE044
are the plane position coordinates of the slope point on the boundary of the seabed geographic entity, respectively,
Figure 894739DEST_PATH_IMAGE045
is the total number of slope points that lie on the boundaries of the seafloor geographic entity.

基于海底地理实体范围

Figure 607480DEST_PATH_IMAGE077
对原始水深模型
Figure 593891DEST_PATH_IMAGE006
进行范 围截取并输出，得到截取后的水深模型
Figure 759293DEST_PATH_IMAGE078
， 其中，
Figure 105830DEST_PATH_IMAGE079
分别为截取后的水深模型
Figure 204236DEST_PATH_IMAGE080
的第
Figure 361548DEST_PATH_IMAGE007
行、第
Figure 764978DEST_PATH_IMAGE008
列的平面位置坐 标值，
Figure 665938DEST_PATH_IMAGE035
为截取后的水深模型
Figure 353271DEST_PATH_IMAGE080
中该平面位置的深度值，截取后的水深模 型见附图6。 Based on the extent of seabed geographic entities
Figure 607480DEST_PATH_IMAGE077
for the original bathymetric model
Figure 593891DEST_PATH_IMAGE006
Perform range interception and output to obtain the intercepted water depth model
Figure 759293DEST_PATH_IMAGE078
, in,
Figure 105830DEST_PATH_IMAGE079
are the intercepted water depth models, respectively
Figure 204236DEST_PATH_IMAGE080
First
Figure 361548DEST_PATH_IMAGE007
row,
Figure 764978DEST_PATH_IMAGE008
the plane position coordinate value of the column,
Figure 665938DEST_PATH_IMAGE035
is the intercepted water depth model
Figure 353271DEST_PATH_IMAGE080
The depth value of the plane position in the middle, and the water depth model after interception is shown in Figure 6.

(ii)形态特征参数提取： (ii) Extraction of morphological feature parameters:

基于截取后的水深模型

Figure 681485DEST_PATH_IMAGE080
应用GIS软件提取该海底地理实体的形态 特征参数
Figure 94184DEST_PATH_IMAGE052
，其中
Figure 533256DEST_PATH_IMAGE011
和
Figure 75095DEST_PATH_IMAGE053
分别代表 该海底地理实体的长度和宽度，
Figure 574210DEST_PATH_IMAGE054
和
Figure 952233DEST_PATH_IMAGE036
分别代表该海底地理实体的最大水深和最小 水深，
Figure 194995DEST_PATH_IMAGE055
代表该海底地理实体的平均坡度，表示为局部地表坡面的倾斜程度，当进行坡 度计算时可表述为简化的差分公式：
Figure 591341DEST_PATH_IMAGE056
其中，
Figure 261357DEST_PATH_IMAGE057
，是x方向高程或水深变化率；
Figure 625211DEST_PATH_IMAGE058
，是y方向高程或水深变化率；得到该 海底地理实体长度
Figure 671665DEST_PATH_IMAGE011
= 2150 m，宽度
Figure 188097DEST_PATH_IMAGE053
= 2060 m，最大水深
Figure 29014DEST_PATH_IMAGE054
= 2350 m，最小水深
Figure 381629DEST_PATH_IMAGE036
= 370 m，平均坡度
Figure 966194DEST_PATH_IMAGE055
= 12.35°。 Based on the intercepted water depth model
Figure 681485DEST_PATH_IMAGE080
Using GIS software to extract the morphological characteristic parameters of the seabed geographic entity
Figure 94184DEST_PATH_IMAGE052
,in
Figure 533256DEST_PATH_IMAGE011
and
Figure 75095DEST_PATH_IMAGE053
represent the length and width of the seabed geographic entity, respectively,
Figure 574210DEST_PATH_IMAGE054
and
Figure 952233DEST_PATH_IMAGE036
represent the maximum and minimum water depths of the seabed geographic entity, respectively,
Figure 194995DEST_PATH_IMAGE055
Represents the average slope of the seabed geographic entity, expressed as the slope of the local surface slope, and can be expressed as a simplified difference formula when calculating the slope:
Figure 591341DEST_PATH_IMAGE056
in,
Figure 261357DEST_PATH_IMAGE057
, is the rate of change in the x -direction elevation or water depth;
Figure 625211DEST_PATH_IMAGE058
, is the rate of change of elevation or water depth in the y direction; get the length of the seabed geographic entity
Figure 671665DEST_PATH_IMAGE011
= 2150 m, width
Figure 188097DEST_PATH_IMAGE053
= 2060 m, maximum water depth
Figure 29014DEST_PATH_IMAGE054
= 2350 m, minimum water depth
Figure 381629DEST_PATH_IMAGE036
= 370 m, average slope
Figure 966194DEST_PATH_IMAGE055
= 12.35°.

基于该海底地理实体的形态特征参数

Figure 337132DEST_PATH_IMAGE059
判定该海底地理实体的等级
Figure 348951DEST_PATH_IMAGE060
为二级和类型
Figure 687397DEST_PATH_IMAGE061
为海山。 Based on the morphological characteristic parameters of the seabed geographic entity
Figure 337132DEST_PATH_IMAGE059
Determining the class of the seabed geographic entity
Figure 348951DEST_PATH_IMAGE060
for secondary and type
Figure 687397DEST_PATH_IMAGE061
for seamounts.

(iii)要素信息表构建： (iii) Construction of element information table:

基于海底地理实体范围

Figure 810074DEST_PATH_IMAGE062
、海底地理实体的形态特征参数
Figure 35519DEST_PATH_IMAGE059
、海 底地理实体的等级
Figure 483818DEST_PATH_IMAGE060
和类型
Figure 545446DEST_PATH_IMAGE061
，构建该海底地理实体的要素信息表，Manifest= {Grade，Type，Area，Parameters}={二级，海山， [5°，15°]，2150m，2060m，2350m，370m， 12.35°}，构建得到的海底地理实体的要素信息表见下表2：Based on the extent of seabed geographic entities
Figure 810074DEST_PATH_IMAGE062
, morphological characteristic parameters of seabed geographic entities
Figure 35519DEST_PATH_IMAGE059
, the level of seabed geographic entities
Figure 483818DEST_PATH_IMAGE060
and type
Figure 545446DEST_PATH_IMAGE061
, construct the feature information table of the seabed geographic entity, Manifest= {Grade, Type, Area, Parameters} = {Secondary, Seamount, [5°, 15°], 2150m, 2060m, 2350m, 370m, 12.35°}, construct The element information table of the obtained seabed geographic entities is shown in Table 2 below:

Figure 471813DEST_PATH_IMAGE081
Figure 471813DEST_PATH_IMAGE081

以上所述实施例仅表达了本发明的几种实施方式，其描述较为具体和详细，但并不能因此而理解为对发明范围的限制。应当指出的是，对于本领域的普通技术人员来说，在不脱离本发明构思的前提下，还可以做出若干变形和改进，这些都属于本发明的保护范围。因此，本发明的保护范围应以所附权利要求为准。The above-mentioned embodiments only represent several embodiments of the present invention, and the descriptions thereof are relatively specific and detailed, but should not be construed as limiting the scope of the invention. It should be pointed out that for those of ordinary skill in the art, without departing from the concept of the present invention, several modifications and improvements can also be made, which all belong to the protection scope of the present invention. Therefore, the scope of protection of the present invention should be determined by the appended claims.

Claims (8)

1. A composite seabed geographic entity progressive decomposition method based on wavelets and filters is characterized by comprising three steps of data preprocessing, composite seabed geographic entity separation and feature extraction: firstly, data preprocessing comprises multi-beam water depth data preprocessing and landform modeling, and a water depth model is constructed; secondly, separating the composite seabed geographic entities, namely performing step-by-step decomposition of the composite terrain, determination of the decomposition grade number and reconstruction of separation results by adopting discrete wavelet transform, so as to separate the seabed geographic entities with different grades; and finally, the characteristic extraction comprises the steps of determining the range of the seabed geographic entity, extracting morphological characteristic parameters and constructing an element information table.
2. The wavelet and filter based progressive decomposition method for composite seafloor geographical entities as claimed in claim 1, wherein the multi-beam depth data preprocessing comprises: CUBE filtering, sound velocity correction and abnormal value elimination processing are carried out on the original multi-beam water depth data to obtain a processed multi-beam water depth data set
Figure 574355DEST_PATH_IMAGE001
Whereinx m Andy m respectively the plane position coordinate values of all the multi-beam sounding points,
Figure 509950DEST_PATH_IMAGE002
the depth value of the multi-beam sounding point,
Figure 139383DEST_PATH_IMAGE003
the number of the depth measurement points is,
Figure 185836DEST_PATH_IMAGE004
and
Figure 702268DEST_PATH_IMAGE003
are all natural numbers.
3. The wavelet and filter based composite seafloor geographical entity progressive decomposition method of claim 2, wherein the topographic modeling: multi-beam water depth data set based on processing
Figure 808765DEST_PATH_IMAGE001
Constructing and obtaining an original water depth model by adopting a spline function interpolation method
Figure 895800DEST_PATH_IMAGE005
WhereinX s,l andY s,l respectively the original water depth model
Figure 480366DEST_PATH_IMAGE006
To (1) a
Figure 116883DEST_PATH_IMAGE007
Line and first
Figure 380899DEST_PATH_IMAGE008
The plane position coordinate values of the columns,
Figure 470078DEST_PATH_IMAGE009
as an original water depth model
Figure 858334DEST_PATH_IMAGE006
The depth value of the location in (a),
Figure 349358DEST_PATH_IMAGE010
and
Figure 282810DEST_PATH_IMAGE011
respectively the total row number and the total column number of the original water depth model,
Figure 859285DEST_PATH_IMAGE007
、
Figure 785652DEST_PATH_IMAGE008
、
Figure 380451DEST_PATH_IMAGE010
and
Figure 999651DEST_PATH_IMAGE011
are all natural numbers.
4. A wavelet and filter based composite seafloor geographical entity progressive decomposition method as claimed in claim 1 or 3, wherein the discrete wavelet transform is used for progressive decomposition of composite terrain: based on original water depth model
Figure 797843DEST_PATH_IMAGE006
Performing discrete wavelet transform, combining a Mallat algorithm with a filter to realize wavelet multi-scale analysis, decomposing the composite terrain into low-frequency terrain approximate components and high-frequency terrain detail components, decomposing the approximate components into lower-level terrain approximate components and terrain detail components each time, and keeping the total data unchanged; the decomposition algorithm is expressed as the formula:
Figure 544213DEST_PATH_IMAGE012
wherein,
Figure 744250DEST_PATH_IMAGE013
in order to disperse the number of the sample data,
Figure 534351DEST_PATH_IMAGE014
and
Figure 819839DEST_PATH_IMAGE015
low-pass and high-pass filter coefficients are used for the decomposition process,
Figure 390805DEST_PATH_IMAGE016
and
Figure 710928DEST_PATH_IMAGE017
are respectively the first
Figure 157084DEST_PATH_IMAGE018
And (3) terrain approximate components and terrain detail components obtained by level wavelet decomposition.
5. The wavelet and filter based composite seafloor geographical entity progressive decomposition method of claim 4, wherein the decomposition level determination and separation result reconstruction: based on decomposed terrain approximation components
Figure 195447DEST_PATH_IMAGE016
And topographic detail component
Figure 532887DEST_PATH_IMAGE017
Determining the number of decomposition steps based on the frequency analysis information
Figure 691205DEST_PATH_IMAGE019
And reconstructing the separation result, wherein the reconstruction formula is as follows:
Figure 823109DEST_PATH_IMAGE020
wherein
Figure 817610DEST_PATH_IMAGE021
and
Figure 709474DEST_PATH_IMAGE022
are respectively as
Figure 473031DEST_PATH_IMAGE023
And
Figure 41415DEST_PATH_IMAGE024
the conjugate of (2) is to repeat the coefficients of each filter bank, and finally the separated water depth model is obtained
Figure 523212DEST_PATH_IMAGE025
And
Figure 454652DEST_PATH_IMAGE026
thereby separating different levels of sub-sea geographic entities.
6. The wavelet and filter based progressive decomposition method of composite seabed geographic entity as claimed in claim 5, wherein said seabed geographic entity range is determined by:
(a) water depth model based on separation
Figure 338295DEST_PATH_IMAGE025
According to the depth of water of the seabed geographic entity
Figure 812001DEST_PATH_IMAGE027
Determining the range of the seabed geographic entity
Figure 62985DEST_PATH_IMAGE028
Wherein
Figure 545919DEST_PATH_IMAGE029
and
Figure 284068DEST_PATH_IMAGE030
respectively are the plane position coordinate values of the water depth point on the seabed geographic entity boundary,
Figure 709102DEST_PATH_IMAGE031
the total number of water depth points on the seabed geographic entity boundary; based on seabed geographic entity scope
Figure 431070DEST_PATH_IMAGE032
For the original water depth model
Figure 202848DEST_PATH_IMAGE006
Range interception and output are carried out to obtain an intercepted water depth model
Figure 326662DEST_PATH_IMAGE033
WhereinX s,l andY s,l respectively a water depth model after cutting
Figure 142172DEST_PATH_IMAGE034
To (1) a
Figure 603633DEST_PATH_IMAGE007
Go, first
Figure 428370DEST_PATH_IMAGE008
The coordinate values of the plane positions of the rows,
Figure 141111DEST_PATH_IMAGE035
for the water depth model after cutting
Figure 143833DEST_PATH_IMAGE034
The depth value of the position of the plane in question,
Figure 309235DEST_PATH_IMAGE036
for the water depth model after cutting
Figure 186930DEST_PATH_IMAGE034
The minimum water depth of the water in the water tank,
Figure 285336DEST_PATH_IMAGE037
for the water depth model after cutting
Figure 990118DEST_PATH_IMAGE034
The maximum water depth of the water to be treated,
Figure 642816DEST_PATH_IMAGE010
and
Figure 543776DEST_PATH_IMAGE011
respectively a water depth model after cutting
Figure 231110DEST_PATH_IMAGE034
The total number of rows and the total number of columns,
Figure 77099DEST_PATH_IMAGE007
、
Figure 217094DEST_PATH_IMAGE008
、
Figure 656165DEST_PATH_IMAGE010
and
Figure 198005DEST_PATH_IMAGE011
are all natural numbers;
(b) water depth model based on separation
Figure 447852DEST_PATH_IMAGE026
To find a model of the gradient
Figure 340721DEST_PATH_IMAGE038
Wherein
Figure 583484DEST_PATH_IMAGE039
respectively being a model of gradient
Figure 494677DEST_PATH_IMAGE040
To (1) a
Figure 430272DEST_PATH_IMAGE007
Line and first
Figure 810438DEST_PATH_IMAGE008
The plane position coordinate values of the columns,
Figure 607624DEST_PATH_IMAGE041
is a slope model
Figure 858476DEST_PATH_IMAGE040
A slope value of the plane position; based on gradient model
Figure 964973DEST_PATH_IMAGE040
According to the gradient range of the seabed geographic entity
Figure 830771DEST_PATH_IMAGE042
Determining the range of the seabed geographic entity
Figure 415336DEST_PATH_IMAGE043
Wherein
Figure 51854DEST_PATH_IMAGE044
and
Figure 63672DEST_PATH_IMAGE045
respectively the plane position coordinate values of the gradient points on the boundary of the seabed geographic entity,
Figure 903584DEST_PATH_IMAGE046
the total number of slope points on the seabed geographic entity boundary; based on seabed geographic entity scope
Figure 291840DEST_PATH_IMAGE047
For the original water depth model
Figure 517285DEST_PATH_IMAGE006
Range interception is carried out and output is carried out to obtain an intercepted water depth model
Figure 480430DEST_PATH_IMAGE048
Wherein
Figure 791326DEST_PATH_IMAGE049
respectively a water depth model after cutting
Figure 983273DEST_PATH_IMAGE050
To (1) a
Figure 79536DEST_PATH_IMAGE007
Line and first
Figure 433157DEST_PATH_IMAGE008
The plane position coordinate values of the columns,
Figure 231349DEST_PATH_IMAGE035
for the water depth model after cutting
Figure 226986DEST_PATH_IMAGE050
The depth value of the position of the plane in question,
Figure 679221DEST_PATH_IMAGE051
for the water depth model after cutting
Figure 469322DEST_PATH_IMAGE050
The minimum slope of the slope,
Figure 754810DEST_PATH_IMAGE052
for the water depth model after cutting
Figure 304871DEST_PATH_IMAGE050
The maximum slope of the slope,
Figure 359415DEST_PATH_IMAGE010
and
Figure 320418DEST_PATH_IMAGE011
respectively a water depth model after cutting
Figure 342469DEST_PATH_IMAGE050
The total number of rows and the total number of columns,
Figure 148751DEST_PATH_IMAGE007
、
Figure 323381DEST_PATH_IMAGE008
、
Figure 455285DEST_PATH_IMAGE010
and
Figure 466097DEST_PATH_IMAGE011
are all natural numbers.
7. The wavelet and filter based composite seafloor geographical entity progressive decomposition method as claimed in claim 6, wherein the morphological feature parameter extraction: water depth model based on intercepted water depth
Figure 76070DEST_PATH_IMAGE053
Extracting morphological characteristic parameters of the seabed geographic entity by using GIS software
Figure 370785DEST_PATH_IMAGE054
Wherein
Figure 925788DEST_PATH_IMAGE011
And
Figure 673164DEST_PATH_IMAGE055
respectively representing the length and width of the sub-sea geographic entity,
Figure 86828DEST_PATH_IMAGE056
and
Figure 986782DEST_PATH_IMAGE036
respectively representing the maximum and minimum water depths of the sub-sea geographic entity,
Figure 460488DEST_PATH_IMAGE057
the average grade representing the seafloor geographical entity, expressed as the degree of slope of the local surface slope, may be expressed as a simplified difference formula when performing the grade calculation:
Figure 429581DEST_PATH_IMAGE058
wherein,
Figure 646936DEST_PATH_IMAGE059
is prepared fromxElevation or depth of water rate of change;
Figure 899932DEST_PATH_IMAGE060
is prepared fromyElevation or depth of water rate of change; morphological characteristic parameter based on the seabed geographic entity
Figure 544540DEST_PATH_IMAGE061
Determining a rank of the subsea geographic entity
Figure 266508DEST_PATH_IMAGE062
And type
Figure 38286DEST_PATH_IMAGE063
。
8. The wavelet and filter based composite seafloor geographical entity progressive decomposition method as claimed in claim 7, wherein the element information table constructs: based on seabed geographic entity scope
Figure 630942DEST_PATH_IMAGE064
Morphological characteristic parameter of seabed geographic entity
Figure 446451DEST_PATH_IMAGE061
Grade of seabed geographic entity
Figure 907913DEST_PATH_IMAGE062
And type
Figure 467070DEST_PATH_IMAGE063
And constructing an element information table of the seabed geographic entity
Figure 179811DEST_PATH_IMAGE065
。
CN202210732260.2A 2022-06-27 2022-06-27 Wavelet and filter-based composite seabed geographic entity progressive decomposition method Pending CN114820951A (en)

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