CN118469886B - Method for adaptively adjusting image contrast based on image brightness information - Google Patents
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Abstract
The invention provides a method for adaptively adjusting image contrast based on image brightness information, which comprises the steps of extracting the brightness information of an input image; carrying out brightness distribution statistics on the brightness information, and judging the type of an input image according to a preset threshold value: low brightness, high highlighting, too high contrast, or too low contrast, etc.; determining a brightness adjusting curve according to the image type, and adjusting the contrast point by point; and dividing the adjusted brightness information by the brightness information of the input image to obtain gain adjustment coefficients of all pixel points, and mapping R, G, B three channels of the input image respectively.
Description
Technical Field
The invention relates to the technical field of image processing. And more particularly to a method for adaptively adjusting image contrast based on image brightness information.
Background
The development of the information age is very new, images are one of important sources for people to acquire information, the requirements of people on image quality are higher and higher, and image contrast is an important index of the performance of various electronic video devices. Image contrast refers to the measurement of the different brightness levels between the brightest white and darkest black of a bright-dark region in an image, i.e., the magnitude of the gray contrast of an image. The larger the difference range represents the higher the contrast ratio, and the smaller the difference range represents the lower the contrast ratio. The influence of contrast on visual effect is very critical, and in general, the larger the contrast is, the clearer and more striking the image is.
The high contrast is helpful for the definition, detail representation and gray level representation of the image. However, too high a contrast ratio tends to make the image show a rough brightness, even a part of details is lost, and too low a contrast ratio tends to make the whole picture show a gray state. For example, when a user takes a picture in daily life, the phenomenon that a shot image is unclear in dark part, low in overall brightness, unobvious in detail features of the image and the like often occurs due to light, equipment and the like. It is therefore necessary to adjust the contrast of the image appropriately according to the content of the image so that the image can display as vivid and rich details as possible.
The invention designs a method for adaptively adjusting the image contrast based on the image brightness information, which can effectively adjust the image contrast according to different image contents, has high flexibility, can keep rich texture details of the image and achieves better visual effect.
Disclosure of Invention
The invention provides a method for adaptively adjusting image contrast based on image brightness information, which comprises the following steps:
Step1, extracting brightness information of an input image;
Step 2, carrying out brightness distribution statistics on the brightness information, and judging the type of an input image according to a preset threshold value: low brightness, high highlighting, too high contrast or too low contrast;
step 3, determining a brightness adjusting curve according to the type of the image, and carrying out contrast adjustment point by point;
and 4, dividing the adjusted brightness information with the brightness information of the input image to obtain gain adjustment coefficients of all pixel points, and mapping R, G, B three channels of the input image respectively.
Further, step 1 includes:
calculating brightness information of each pixel point to obtain initial brightness information of the input image ，
，
Wherein, R, G, B channels of brightness information of the input image respectively;
For a pair of Normalization processing is carried out to obtain the brightness information of the input image：
，
Wherein, Representing the maximum initial luminance among all pixels of the input image,。
Further, step 2 includes:
to make the brightness interval Aliquoting according to brightness informationConstruction of luminance histogramCounting the number of pixel points in each brightness interval，Taking out，Wherein, the method comprises the steps of, wherein,Bit width representing input image according to luminance histogramCalculated to be located atLuminance value at split positionThis luminance value reflects the luminance distribution of the image,Typical values range from 80, 99;
When (when) When the input image is considered to be dark as a whole, the input image is judged to be a low-brightness image; when (when)In this case, the input image is considered to be bright as a whole, and the image is determined to be a highlight image,Respectively a preset lower limit and an upper limit of a brightness threshold;
When (when) Further calculating the luminance histogramVariance of (2)When (when)Less than a preset variance adjustment thresholdWhen the input image is judged to be too low in contrast, the whole picture is considered to be in a faded appearance; when (when)Greater than a preset variance adjustment thresholdWhen the image is considered to be too dark and too bright, the contrast ratio of the input image is judged to be too high; when (when)In this case, the contrast of the input image is considered to be moderate, and contrast adjustment is not required.
In one case, step 3 includes:
when the input image is determined to be a low-brightness image, the brightness information is plotted as follows And (3) overall brightening:
，
Parameters (parameters) Together determine the degree of brightness of the image, wherein,The upper limit and the lower limit of the output brightness of the image are respectively determined for preset fixed parameters, and the preset fixed parameters are set according to specific lightening requirements, so that the overflow and the truncation of the image data are avoided, and the requirements are met；Is in combination withThe related self-adaptive adjustment parameters determine the brightness of the intermediate gray level and should satisfyThe calculation is as follows:
Wherein, the method comprises the steps of, wherein, For a preset curve slope and deviation value,Constant greater than 5, offsetShould satisfy。
In another case, step 3 includes:
When the input image is determined to be a highlight image, the brightness information is compared with the brightness information And (3) carrying out integral darkening:
，
Parameters (parameters) Together determine the degree of darkness of the image, wherein,The upper limit and the lower limit of the output brightness of the image are respectively determined for preset fixed parameters, and the image is set according to specific dimming requirements, so as to avoid overflow and truncation of the image data and meet the requirements of；Is in combination withThe related self-adaptive adjustment parameters determine the darkness degree of the middle gray level and should satisfyThe calculation is as follows: Wherein, the method comprises the steps of, wherein, The values of the slope and the deviation value of the preset curve are within the ranges of。
In yet another case, step 3 includes:
determining the inflection point of S curve by the following linear function when the contrast of input image is too low or too high ：
，
Wherein, For a preset slope and deviation value,The value range is 0.8-1,The value range is 0-0.2;
respectively counting inflection points of brightness information at S curve Variance of pixel groups on both sides: assume that the satisfaction isThe variance of the pixel groups is statisticallySatisfies the following conditionsThe variance of the pixel groups is statistically：
(1) When the contrast of the input image is too low, the picture presents a gray state, and the S curve is utilized to control the brightness informationContrast enhancement is performed, and an S curve is constructed according to the following formula:
，
wherein, To avoid overflow and truncation of image data for preset fixed parametersA constant set to not more than 1; a constant not greater than 0.05 is set to prevent the gradient of the low brightness part of the image from reversing, thereby meeting the requirements of ；Is in combination withRelated adaptive tuning parameters determine inflection pointsThe brightness of the right input data; Is in combination with Related adaptive tuning parameters determine inflection pointsThe degree of darkness of the left-hand input data,、Should satisfyThe specific calculation is as follows:
，
，
wherein, Is the slope of two sets of preset curves,Is a constant that is greater than 1.5,Is a constant of less than 0.4,Is a preset two sets of curve deviation values,The range of the values is as follows，The range of the values is as follows；
(2) When the contrast of the input image is too high, the picture presents a state of over dark and over bright, and part of details are lost, and at the moment, the brightness information is properly reduced by utilizing an inverse S curveIs used for the contrast ratio of (a), the reverse S curve is constructed as follows:
，
wherein, To avoid overflow and truncation of image data for preset fixed parametersA constant set to not more than 1; a constant not greater than 0.05 is set to prevent the gradient of the low brightness part of the image from reversing, thereby meeting the requirements of ；Is in combination withRelated adaptive tuning parameters determine inflection pointsThe degree of darkness of the right-hand input data,Is in combination withRelated adaptive tuning parameters determine inflection pointsThe brightness of the left-hand input data,Satisfy the following requirementsThe specific calculation is as follows:
，
，
wherein, Is the slope of two sets of preset curves,Is a constant of less than 0.8,Is a constant that is greater than 1.1,Is a preset two sets of curve deviation values,
The range of the values is as follows，The range of the values is as follows。
Further, to control the degree of adjusting the image contrast, a contrast adjusting global coefficient is introducedCalculating to obtain output brightness information
，
Wherein, For the output after the contrast adjustment in the above step3,For the final output of luminance information.
Further, step 4 includes:
Will finally output brightness information And luminance informationDividing to obtain gain adjustment coefficients of all pixel points of the image：
，
Mapping R, G, B three channels of the input image respectively to obtain a final image：
。
Drawings
FIG. 1 is a flow chart of image contrast adjustment of the present invention;
FIG. 2 is a diagram showing a histogram distribution of the present invention;
FIG. 3 is a diagram showing a brightness map of a low-brightness image according to the present invention;
FIG. 4 is a graph showing the contrast adjustment of the brightness of a low-brightness image using the brightness map of the low-brightness image according to the present invention;
FIG. 5 is a schematic diagram of a brightness map of a highlight image according to the present invention;
FIG. 6 is a graph showing the contrast adjustment of the highlight image using the highlight image brightness map curve according to the present invention;
FIG. 7 is a diagram illustrating a low contrast image brightness map according to the present invention;
FIG. 8 is a graph showing the contrast adjustment of the low-contrast image using the low-contrast image brightness map curve according to the present invention;
FIG. 9 is a diagram of a high contrast image brightness map according to the present invention;
FIG. 10 is a graph showing the contrast adjustment of the high contrast image using the high contrast image brightness map curve according to the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, the present invention provides a method for adaptively adjusting image contrast based on image brightness information, which includes:
Step1, extracting brightness information of an input image;
Step 2, carrying out brightness distribution statistics on the brightness information, and judging the type of an input image according to a preset threshold value: low brightness, high highlighting, too high contrast or too low contrast;
step 3, determining a brightness adjusting curve according to the type of the image, and carrying out contrast adjustment point by point;
and 4, dividing the adjusted brightness information with the brightness information of the input image to obtain gain adjustment coefficients of all pixel points, and mapping R, G, B three channels of the input image respectively.
Referring to fig. 2, the luminance histogram describes the statistical characteristics of each luminance level of an image, and the abscissa thereof is the luminance level of each pixel point in the image, and the ordinate thereof represents the number and frequency of occurrence of pixels having each luminance level in the image. We can determine whether an image is darker or lighter, etc. through the histogram corresponding to the image. Typically, the data in the histogram of a darker picture is concentrated on the left and middle parts, while the data in the overall bright image histogram is concentrated on the right.
In the first embodiment, when it is determined that the input image is a low-luminance image, the luminance information is plotted as followsAnd (3) overall brightening:
，
Parameters (parameters) Together determine the degree of brightness of the image, wherein,The upper and lower limits of the image output brightness are respectively determined for preset fixed parameters, and the image output brightness is set according to specific brightness requirements, so that the overflow and truncation of the image data are usually required to be satisfied；Is in combination withThe related self-adaptive adjustment parameters determine the brightness of the intermediate gray level and should satisfyThe calculation is as follows:
，
wherein, For a preset curve slope and deviation value,Typically a constant greater than 5, offsetShould satisfyA diagram of the brightness map of the low-brightness image is shown in FIG. 3, wherein the broken line is brightness informationThe curve is the output brightness information after brightness improvement. Contrast adjustment of low-brightness images using low-brightness image brightness map curves is shown in fig. 4.
In the second embodiment, when it is determined that the input image is a highlight image, the luminance information is entirely darkened:
，
Parameters (parameters) Together determine the degree of darkness of the image, wherein,The upper limit and the lower limit of the output brightness of the image are respectively determined for preset fixed parameters, and the image is set according to specific dimming requirements, so as to avoid overflow and truncation of the image data and meet the requirements of；Is in combination withThe related self-adaptive adjustment parameters determine the darkness degree of the middle gray level and should satisfyThe calculation is as follows: Wherein, the method comprises the steps of, wherein, The values of the slope and the deviation value of the preset curve are within the ranges ofA schematic diagram of brightness map of a highlight image is shown in FIG. 5, in which the broken line is brightness informationThe curve is the output brightness information after brightness is darkened. Contrast adjustment of the highlight image using the highlight image brightness map curve is shown in fig. 6 for a comparison of effects before and after contrast adjustment.
In a third embodiment, when it is determined that the contrast of the input image is too low or too high, the inflection point of the S-curve is determined by the following linear function：
，
Wherein, Is a preset slope and deviation value.
Respectively counting inflection points of brightness information at S curveVariance of pixel groups on both sides: assume that the satisfaction isThe variance of the pixel groups is statisticallySatisfies the following conditionsThe variance of the pixel groups is statistically：
(1) When the contrast of the input image is too low, the picture presents a gray state, and the S curve is utilized to control the brightness informationContrast enhancement is performed, and an S curve is constructed according to the following formula:
，
wherein, To avoid overflow and truncation of image data for preset fixed parametersA constant set to not more than 1; a constant not greater than 0.05 is set to prevent the gradient of the low brightness part of the image from reversing, thereby meeting the requirements of ；Is in combination withRelated adaptive tuning parameters determine inflection pointsThe brightness of the right input data; Is in combination with Related adaptive tuning parameters determine inflection pointsThe degree of darkness of the left-hand input data,、Should satisfyThe specific calculation is as follows:
，
，
wherein, Is the slope of two sets of preset curves,Is a constant that is greater than 1.5,Is a constant of less than 0.4,Is a preset two sets of curve deviation values,The range of the values is as follows，The range of the values is as followsA schematic diagram of the corresponding brightness map when different inflection points are selected is shown in FIG. 7, wherein the broken line is brightness informationThe curve is the output brightness information after contrast improvement. Contrast adjustment of low contrast images using low contrast image brightness map curves is shown in fig. 8.
(2) When the contrast of the input image is too high, the picture presents a state of over dark and over bright, and part of details are lost, and at the moment, the brightness information is properly reduced by utilizing an inverse S curveIs used for the contrast ratio of (a), the reverse S curve is constructed as follows:
，
wherein, To avoid overflow and truncation of image data for preset fixed parametersA constant set to not more than 1; a constant not greater than 0.05 is set to prevent the gradient of the low brightness part of the image from reversing, thereby meeting the requirements of ；Is in combination withRelated adaptive tuning parameters determine inflection pointsThe degree of darkness of the right-hand input data,Is in combination withRelated adaptive tuning parameters determine inflection pointsThe brightness of the left-hand input data,Satisfy the following requirementsThe specific calculation is as follows:
，
，
wherein, Is the slope of two sets of preset curves,Is a constant of less than 0.8,Is a constant that is greater than 1.1,Is a preset two sets of curve deviation values,The range of the values is as follows，The range of the values is as followsA schematic diagram of the corresponding brightness map when different inflection points are selected is shown in FIG. 9, wherein the broken line is brightness informationThe curve is the output brightness information after the contrast is reduced. Contrast adjustment of high contrast images using high contrast image brightness map curves is shown in fig. 10.
To better control the degree of adjusting image contrast, a contrast adjusting global coefficient is introducedCalculating to obtain output brightness information
，
Wherein, For the output after the contrast adjustment in the above step3,For the final output of luminance information.
Will finally output brightness informationAnd luminance informationDividing to obtain gain adjustment coefficients of all pixel points of the image：
，
Mapping R, G, B three channels of the input image respectively to obtain a final image：
。
It is noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
Although embodiments of the present invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made therein without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (1)
1. A method for adaptively adjusting image contrast based on image brightness information, comprising:
Step1, extracting brightness information of an input image;
Step 2, carrying out brightness distribution statistics on the brightness information, and judging the type of an input image according to a preset threshold value: low brightness, high highlighting, too high contrast or too low contrast;
step 3, determining a brightness adjusting curve according to the type of the image, and carrying out contrast adjustment point by point;
Step 4, dividing the adjusted brightness information with the brightness information of the input image to obtain gain adjustment coefficients of all pixel points, and mapping R, G, B three channels of the input image respectively;
The step 1 comprises the following steps:
calculating brightness information of each pixel point to obtain initial brightness information of the input image ，
，
Wherein, R, G, B channels of brightness information of the input image respectively;
For a pair of Normalization processing is carried out to obtain the brightness information of the input image：
，
Wherein, Representing the maximum initial luminance among all pixels of the input image,；
The step 2 comprises the following steps:
to make the brightness interval Aliquoting according to brightness informationConstruction of luminance histogramCounting the number of pixel points in each brightness interval，Taking out，Wherein, the method comprises the steps of, wherein,Bit width representing input image according to luminance histogramCalculated to be located atLuminance value at split positionThis luminance value reflects the luminance distribution of the image,The value range of (2) is [80, 99];
When (when) When the input image is considered to be dark as a whole, the input image is judged to be a low-brightness image; when (when)In this case, the input image is considered to be bright as a whole, and the image is determined to be a highlight image,Respectively a preset lower limit and an upper limit of a brightness threshold;
When (when) Further calculating the luminance histogramVariance of (2)When (when)Less than a preset variance adjustment thresholdWhen the input image is judged to be too low in contrast, the whole picture is considered to be in a faded appearance; when (when)Greater than a preset variance adjustment thresholdWhen the image is considered to be too dark and too bright, the contrast ratio of the input image is judged to be too high; when (when)When the input image is considered to have moderate contrast, the contrast adjustment is not needed;
The step 3 comprises the following steps:
when the input image is determined to be a low-brightness image, the brightness information is plotted as follows And (3) overall brightening:
，
Parameters (parameters) Together determine the degree of brightness of the image, wherein,The upper limit and the lower limit of the output brightness of the image are respectively determined for preset fixed parameters, and the preset fixed parameters are set according to specific lightening requirements, so that the overflow and the truncation of the image data are avoided, and the requirements are met；Is in combination withThe related self-adaptive adjustment parameters determine the brightness of the intermediate gray level and should satisfyThe calculation is as follows:
，
wherein, For a preset curve slope and deviation value,Constant greater than 5, offsetShould satisfy；
The step 3 comprises the following steps:
When the input image is determined to be a highlight image, the brightness information is compared with the brightness information And (3) carrying out integral darkening:
，
Parameters (parameters) Together determine the degree of darkness of the image, wherein,The upper limit and the lower limit of the output brightness of the image are respectively determined for preset fixed parameters, and the image is set according to specific dimming requirements, so as to avoid overflow and truncation of the image data and meet the requirements of；Is in combination withThe related self-adaptive adjustment parameters determine the darkness degree of the middle gray level and should satisfyThe calculation is as follows:
，
wherein, The values of the slope and the deviation value of the preset curve are within the ranges of；
The step 3 comprises the following steps:
determining the inflection point of S curve by the following linear function when the contrast of input image is too low or too high ：
，
Wherein, For a preset slope and deviation value,The value range is 0.8-1,The value range is 0-0.2;
respectively counting inflection points of brightness information at S curve Variance of pixel groups on both sides: assume that the satisfaction isThe variance of the pixel groups is statisticallySatisfies the following conditionsThe variance of the pixel groups is statistically：
(1) When the contrast of the input image is too low, the picture presents a gray state, and the S curve is utilized to control the brightness informationContrast enhancement is performed, and an S curve is constructed according to the following formula:
，
wherein, To avoid overflow and truncation of image data for preset fixed parametersA constant set to not more than 1; a constant not greater than 0.05 is set to prevent the gradient of the low brightness part of the image from reversing, thereby meeting the requirements of ；Is in combination withRelated adaptive tuning parameters determine inflection pointsThe brightness of the right input data; Is in combination with Related adaptive tuning parameters determine inflection pointsThe degree of darkness of the left-hand input data,、Should satisfyThe specific calculation is as follows:
，
，
wherein, Is the slope of two sets of preset curves,Is a constant that is greater than 1.5,Is a constant of less than 0.4,Is a preset two sets of curve deviation values,The range of the values is as follows，The range of the values is as follows；
(2) When the contrast of the input image is too high, the picture presents a state of over dark and over bright, and part of details are lost, and at the moment, the brightness information is properly reduced by utilizing an inverse S curveIs used for the contrast ratio of (a), the reverse S curve is constructed as follows:
，
wherein, To avoid overflow and truncation of image data for preset fixed parametersA constant set to not more than 1; a constant not greater than 0.05 is set to prevent the gradient of the low brightness part of the image from reversing, thereby meeting the requirements of ；Is in combination withRelated adaptive tuning parameters determine inflection pointsThe degree of darkness of the right-hand input data,Is in combination withRelated adaptive tuning parameters determine inflection pointsThe brightness of the left-hand input data,Satisfy the following requirementsThe specific calculation is as follows:
，
，
wherein, Is the slope of two sets of preset curves,Is a constant of less than 0.8,Is a constant that is greater than 1.1,Is a preset two sets of curve deviation values,The range of the values is as follows，The range of the values is as follows；
To control the degree of adjusting image contrast, a contrast adjusting global coefficient is introducedCalculating to obtain output brightness information
，
Wherein, For the output after the contrast adjustment in the above step3,To output brightness information;
Step 4 comprises:
Will finally output brightness information And luminance informationDividing to obtain gain adjustment coefficients of all pixel points of the image：
，
Mapping R, G, B three channels of the input image respectively to obtain a final image：
。
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