CN111246081B

CN111246081B - Method for simulating low-resolution camera imaging by high-resolution image

Info

Publication number: CN111246081B
Application number: CN201911335915.7A
Authority: CN
Inventors: 聂婷; 陈长征; 李宪圣; 张星祥; 毕国玲; 刘洪兴
Original assignee: Changchun Institute of Optics Fine Mechanics and Physics of CAS
Current assignee: Changchun Institute of Optics Fine Mechanics and Physics of CAS
Priority date: 2019-12-23
Filing date: 2019-12-23
Publication date: 2021-03-23
Anticipated expiration: 2039-12-23
Also published as: CN111246081A

Abstract

The method for simulating the imaging of the low-resolution camera by the high-resolution image, provided by the invention, is a low-resolution image method for simulating the design parameters according to the preset input of the ideal high-resolution image, by combining optical design parameters and CCD size parameters and considering the influence of CCD and optical transfer function sampling on the imaging.

Description

Method for simulating low-resolution camera imaging by high-resolution image

Technical Field

The invention relates to the technical field of computer simulation, in particular to a method for simulating low-resolution camera imaging by using a high-resolution image.

Background

Resolution is an important index parameter of a satellite-borne optical remote sensing system, and due to the long development period and high complexity of a camera, the imaging effect of a story is evaluated according to parameters such as optical design and the like, which is particularly important.

Disclosure of Invention

In view of the above, there is a need to provide a method for simulating low-resolution camera imaging with high-resolution images, which is economical, simple and convenient, and facilitates design optimization of the camera.

In order to achieve the purpose, the invention adopts the following technical scheme:

the invention provides a method for simulating low-resolution camera imaging by a high-resolution image, which comprises the following steps:

inputting an original high-resolution image Img _ high, wherein the size of the image is W x H;

inputting the resolution of the original high-resolution image, recorded as gsd _ high;

inputting the resolution of a low-resolution image to be fitted, and recording as gsd _ low;

inputting the CCD size of a simulated low-resolution camera, recording the CCD size as CCD _ size and optical PSF size, recording the PSF _ size and the optical transfer function of the camera to be simulated as PSF _ OP;

calculating a proportionality coefficient k of gsd _ high and gsd _ low, wherein k is gsd _ low/gsd _ high;

if k is an integer, define num _ repeat as k; if k is a decimal, taking a decimal point of k and counting the number of n to obtain k1, defining that n _ ccd is k1 × 10n, and n _ psf is 10 n;

calculating the greatest common divisor r of n _ ccd and n _ psf, and calculating num _ response which is n _ ccd/r;

determining the size of a low-resolution image point diffusion function map Img _ psf, wherein row is 3 × num _ repeat, column low is 3 × num _ repeat, and the initial value is assigned to 0;

assigning the central position of Img _ psf, wherein the specific assignment ranges from num _ response +1 to num _ response × 2 rows, num _ response +1 to num _ response columns, and the regions are assigned as 1;

the Img _ psf is normalized by a first formula,

the first formula is: img _ psf ═ Img _ psf/sum (Img _ psf); wherein sum (Img _ psf) represents the sum of point spread functions;

obtaining an initial resolution image Img _ con by using a high resolution image convolution point spread function Img _ psf by using a second formula, wherein the second formula is as follows:

img _ con ═ conv2(Img _ high, Img _ psf, 'same'), where conv2 represents the convolution operation in the matlab tool two-dimensional;

down-sampling the image img _ conv by n times to obtain an image img _ low0 without considering the actual optical transfer function, wherein n is 1/num _ response; img _ low0 ═ imresize (img _ conv, n, 'biliar');

wherein, imresize represents an interpolation tool in MATLAB tool, 'bilinar' is cubic interpolation;

calculating num _ reset 1 according to the CCD size of the input simulated low-resolution camera and the optical transfer function of the camera to be simulated, wherein num _ reset 1 is CCD _ size/psf _ size;

according to the img _ low0 interpolation, aligning num _ response 1 with the size of psf and obtaining an image img _ res according to a third formula:

the third formula is img _ res ═ imres (img _ low0, num _ repeat 1, 'bilinar'), where imres represents one of the MATLAB tools and 'bilinar' is cubic interpolation;

convolving the image img _ res with the input optical PSF _ OP to obtain an image img _ conv2, img _ conv2 being conv2(img _ res, PSF _ OP, 'same'); wherein conv2 represents the convolution operation in two dimensions of matlab tool;

sampling img _ conv2 to obtain an output analog low-resolution image img _ low, wherein img _ low is imresize (img _ conv2,1/num _ response, 'biliner'); wherein, imresize represents one of the interpolation tools in MATLAB tool, 'bilinar' is cubic interpolation.

The invention adopts the technical scheme that the method has the advantages that:

Drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.

Fig. 1 is a flowchart illustrating steps of a method for simulating low-resolution camera imaging by using a high-resolution image according to an embodiment of the present invention.

Fig. 2 is an input original high resolution image provided by an embodiment of the present invention.

Fig. 3 is a diagram illustrating PSF _ OP of an optical transfer function of a camera to be simulated according to an embodiment of the invention.

FIG. 4 shows that the resolution of 5m is obtained without considering the optical transfer function according to the embodiment of the present invention.

FIG. 5 is a low resolution image of an output simulation obtained by an embodiment of the present invention.

Detailed Description

The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

Referring to fig. 1, a flowchart of steps of a method for simulating low-resolution camera imaging by using a high-resolution image according to an embodiment of the present invention includes the following steps:

step S110: an original high-resolution image Img _ high is input, and the image size is W x H.

Referring to fig. 2, the original high resolution image input by the embodiment of the present invention has an image size of 4000 × 5000, and the resolution image is 1 m.

Step S120: the resolution of the original high resolution image is input, noted gsd _ high.

Step S130: the resolution of the low resolution image to be fitted is input, noted gsd _ low.

Step S140: the CCD dimensions of the simulated low resolution camera, denoted as CCD _ size and optical PSF size, denoted PSF _ size and the optical transfer function of the camera to be simulated, denoted PSF _ OP.

Please refer to fig. 3, which is a diagram illustrating PSF _ OP of an optical transfer function of a camera to be simulated according to an embodiment of the present invention.

Step S150: calculating a proportionality coefficient k of gsd _ high and gsd _ low, wherein k is gsd _ low/gsd _ high;

if k is an integer, define num _ repeat as k; when k is a decimal, k is counted to n digits to obtain k1, and n _ ccd is defined as k1 × 10n, and n _ psf is defined as 10 n.

Step S160: the greatest common divisor r of n _ ccd and n _ psf is calculated, and num _ response which is n _ ccd/r is calculated.

Step S170: and determining the size of the low-resolution image point diffusion function map Img _ psf, wherein row is 3 × num _ repeat, column low is 3 × num _ repeat, and the initial value is set to 0.

Step S180: the central position of Img _ psf is assigned, specifically, the assigned values range from num _ response +1 to num _ response × 2 rows, and num _ response +1 to num _ response columns, and the assigned values of the regions are all 1.

Step S190: carrying out normalization processing on the Img _ psf by adopting a first formula, wherein the first formula is as follows: img _ psf ═ Img _ psf/sum (Img _ psf); where sum (Img _ psf) represents the sum of the point spread functions.

Step S210: obtaining an initial resolution image Img _ con by using a high resolution image convolution point spread function Img _ psf by using a second formula, wherein the second formula is as follows:

img _ con ═ conv2(Img _ high, Img _ psf, 'same'), where conv2 represents the convolution operation in the matlab tool two dimensions.

Step S220: down-sampling the image img _ conv by n times to obtain an image img _ low0 without considering the actual optical transfer function, wherein n is 1/num _ response; img _ low0 ═ imresize (img _ conv, n, 'biliar');

wherein, imresize represents one of the interpolation tools in MATLAB tool, 'bilinar' is cubic interpolation.

Referring to fig. 4, an image with a resolution of 5m, 800 x 1000, was obtained for an embodiment of the present invention without considering the optical transfer function.

Step S230: num _ reset 1 is calculated according to the CCD size of the input simulated low resolution camera and the optical transfer function of the camera to be simulated, num _ reset 1 is CCD _ size/psf _ size.

Step S240: according to the img _ low0 interpolation, aligning num _ response 1 with the size of psf and obtaining an image img _ res according to a third formula;

the third formula is img _ res ═ imres (img _ low0, num _ repeat 1, 'bilinar'), where imres represents one of the MATLAB tools and 'bilinar' is cubic interpolation.

Step S250: convolving the image img _ res with the input optical PSF _ OP to obtain an image img _ conv2, img _ conv2 being conv2(img _ res, PSF _ OP, 'same'); wherein conv2 represents the convolution operation in two dimensions of the matlab tool.

Step S260: sampling img _ conv2 to obtain an output analog low-resolution image img _ low, wherein img _ low is imresize (img _ conv2,1/num _ response, 'biliner'); wherein, imresize represents one of the interpolation tools in MATLAB tool, 'bilinar' is cubic interpolation.

Referring to fig. 5, the output analog low-resolution image img _ low obtained through the above steps is an image with a resolution of 5m and a size of 800 × 1000.

Of course, the method for simulating low-resolution camera imaging by using high-resolution images of the present invention may also have various changes and modifications, and is not limited to the specific structure of the above-mentioned embodiments. In conclusion, the scope of the present invention should include those changes or substitutions and modifications which are obvious to those of ordinary skill in the art.

Claims

1. a method for high-resolution image simulation low-resolution camera imaging, is characterized in that, comprises the following steps:

Input the original high-resolution image Img_high, the image size is W*H;

Input the resolution of the original high-resolution image, denoted as gsd_high;

Enter the resolution of the low-resolution image to be fitted, denoted as gsd_low;

Input the CCD size of the simulated low-resolution camera, denoted as ccd_size and optical psf size, denoted as psf_size and the optical transfer function of the camera to be simulated, denoted as PSF_OP;

Calculate the proportional coefficient k of gsd_high and gsd_low, k=gsd_low/gsd_high;

If k is an integer, define num_resample=k; if k is a decimal, take k to n digits after the decimal point to get k1, define n_ccd=k1*10n, n_psf=10n;

Calculate the greatest common divisor r of n_ccd and n_psf, and calculate num_resample, the num_resample=n_ccd/r;

Determine the size of the low-resolution image point spread function map Img_psf, where row=3*num_resample, column low=3*num_resample, and the initial value is assigned 0;

Assign the center position of Img_psf, the specific assignment range is from row num_resample+1 to num_resample*2, and column num_resample+1 to 2*num_resample, and this area is assigned a value of 1;

Img_psf is normalized by the first formula,

The first formula is: normalize Img_psf as the quotient of the point spread function and the sum of the point spread function sum(Img_psf);

Adopt the second formula to obtain the initial resolution image img_conv with the high-resolution image convolution point spread function Img_psf, and the second formula is as follows:

img_conv=conv2(Img_high,Img_psf,'same'), where conv2 represents the convolution operation on the two-dimensional matlab tool;

Downsample the image img_conv by n times to obtain the image img_low0 without considering the actual optical transfer function, n=1/num_resample; img_low0=imresize(img_conv,n,'bilinear');

Among them, imresize represents an interpolation tool in the MATLAB tool, and 'bilinear' is cubic interpolation;

According to the CCD size of the input simulated low-resolution camera and the optical transfer function of the camera to be simulated, calculate num_resample1, num_resample1=ccd_size/psf_size;

According to the img_low0 interpolation, align num_resample1 with the size of psf and get the image img_res according to the third formula:

The third formula is img_res=imresize(img_low0,num_resample1,'bilinear');

Convolve the image img_res with the input optical PSF_OP to obtain the image img_conv2, img_conv2=conv2(img_res,PSF_OP,'same'); where, conv2 represents the convolution operation on the two-dimensional matlab tool;

Sampling img_conv2 to obtain an output simulated low-resolution image img_low, img_low=imresize(img_conv2,1/num_resample,'bilinear').