CN113989127A - Image contrast adjusting method, system, equipment and computer storage medium - Google Patents
Image contrast adjusting method, system, equipment and computer storage medium Download PDFInfo
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Abstract
The application discloses an image contrast adjusting method, system, equipment and computer storage medium, which are used for obtaining an image to be adjusted; dividing an image to be adjusted into a preset number of sub-images; acquiring target contrast characteristic information of each sub-image; determining a target gray value corresponding to each target contrast characteristic information in the gray value of the image to be adjusted; and taking the target gray value as a gray threshold, and performing contrast adjustment on the image to be adjusted based on the gray threshold to obtain the target image. In the application, because the contrast characteristic information can reflect the contrast information of the sub-image, the target gray value is determined subsequently, and if the target gray value is used as the gray threshold, the gray threshold can be matched with the contrast information of the image to be adjusted, so that if the contrast adjustment is performed on the image to be adjusted based on the gray threshold, the contrast adjustment is performed on the image equivalently according to the contrast information of the image, and the adjustment process can be ensured to be adaptive to the image.
Description
Technical Field
The present application relates to the field of image adjustment technologies, and in particular, to a method, a system, a device, and a computer storage medium for adjusting image contrast.
Background
Contrast refers to the measurement of different brightness levels between the brightest white and darkest black of bright and dark regions in an image, and the larger the difference range is, the larger the contrast is, and the smaller the difference range is, the smaller the contrast is. In the process of acquiring the image, due to the influence of factors such as ambient illumination and the like, the image has the condition of unsatisfactory contrast, so that in the application process of the image, in order to enhance the visual effect of the image and facilitate the observation of the image by human eyes, the contrast of the image can be improved through a contrast enhancement technology, so that a target object in an original dark image can be obviously distinguished, and the details are clear and distinguishable; for example, the contrast of the image may be adjusted through a linear stretching algorithm, however, in the adjustment process, after the image to be adjusted is replaced, a picture jump phenomenon caused by insufficient stretching or excessive stretching may occur, which affects user experience.
In summary, how to improve the adaptivity of the image contrast adjustment method is a problem to be solved urgently by those skilled in the art.
Disclosure of Invention
The present application aims to provide an image contrast adjusting method, which can solve the technical problem of how to improve the adaptivity of the image contrast adjusting method to a certain extent. The application also provides an image contrast adjustment system, an image contrast adjustment device and a computer-readable storage medium.
In order to achieve the above purpose, the present application provides the following technical solutions:
an image contrast adjustment method comprising:
acquiring an image to be adjusted;
dividing the image to be adjusted into a preset number of sub-images;
acquiring target contrast characteristic information of each sub-image;
determining a target gray value corresponding to each target contrast characteristic information in the gray values of the images to be adjusted;
and taking the target gray value as a gray threshold, and carrying out contrast adjustment on the image to be adjusted based on the gray threshold to obtain a target image.
Preferably, the determining a target gray value corresponding to each target contrast characteristic information in the gray values of the image to be adjusted includes:
acquiring a first corresponding relation between contrast characteristic information and a stretching proportion coefficient;
acquiring a second corresponding relation between the stretching proportion coefficient and the accumulated gray probability density value;
determining a target stretching proportion coefficient corresponding to each target contrast characteristic information based on the first corresponding relation;
determining a target gray probability density value corresponding to each target stretching proportion coefficient based on the second corresponding relation;
determining a target gray level corresponding to the target gray probability density value, and determining a gray value corresponding to the target gray level as the target gray value;
wherein the stretching proportion coefficient comprises the ratio of the number of target pixels to the total number of pixels of the image; the cumulative grayscale probability density value comprises a sum of the grayscale probability densities for the target pixel; the target pixels include pixels having a gray value equal to or less than a cutoff gray value.
Preferably, the determining a target stretch scaling factor corresponding to each target contrast characteristic information based on the first corresponding relationship includes:
determining a median value in the target contrast characteristic information;
dividing the target contrast characteristic information larger than the median into first-class contrast characteristic information;
dividing the target contrast characteristic information which is less than or equal to the median into second-class contrast characteristic information;
determining a first stretching proportion coefficient corresponding to each first-class contrast characteristic information based on the first corresponding relation, and taking a difference value between 1 and the first stretching proportion coefficient as the target stretching proportion coefficient corresponding to the first-class contrast characteristic information;
and determining a second stretching proportion coefficient corresponding to each second type of contrast characteristic information based on the first corresponding relation, and directly taking the second stretching proportion coefficient as the target stretching proportion coefficient corresponding to the second type of contrast characteristic information.
Preferably, the performing contrast adjustment on the image to be adjusted based on the gray threshold includes:
determining a stretching multiple and a brightness gain value based on the adjacent gray level threshold values;
determining a first type of pixels with gray values between adjacent gray threshold values in the image to be adjusted;
and adjusting the gray value of the first type of pixels based on the stretching multiple and the brightness gain value.
Preferably, the determining the stretching factor and the brightness gain value based on the adjacent gray level threshold values includes:
determining the stretching multiple and the brightness gain value based on the adjacent gray threshold values through an adjustment coefficient determination formula;
the adjustment coefficient determination formula includes:
wherein a represents the stretch ratio and b represents the brightness gain value; outR、OutLRepresenting a preset gray value; inRThe gray threshold value with a larger value in the adjacent gray threshold values is represented; inLThe gray threshold value with a smaller value is represented in the adjacent gray threshold values;
the adjusting the gray value of the first type of pixels based on the stretching multiple and the brightness gain value comprises:
adjusting the gray value of the first type of pixels based on the stretching multiple and the brightness gain value through a contrast adjustment formula;
the contrast adjustment formula includes:
imOut(x,y)＝a*imIn(x,y)+b；
wherein imOut (x, y) represents the gray value after adjustment of the first type of pixels; imIn (x, y) represents the original gray value of the first type of pixel; (x, y) represents the position coordinates of the first type of pixels in the image to be adjusted.
Preferably, the dividing the image to be adjusted into a preset number of sub-images includes:
dividing the image to be adjusted into a preset number of sub-images by using an image segmentation method based on a threshold value;
wherein the types of the threshold values comprise a median value, a mean value, a value determined based on a large law method, a value determined based on a histogram doublet method, and a value determined based on an iteration method.
Preferably, the types of the target contrast characteristic information include variance, standard deviation, weber contrast, and root mean square contrast.
Preferably, before dividing the image to be adjusted into a preset number of sub-images, the method further includes:
acquiring the number of preset gray level threshold values;
and taking the number of the preset gray threshold values as the preset number.
An image contrast adjustment system, comprising:
the image acquisition module is used for acquiring an image to be adjusted;
the image dividing module is used for dividing the image to be adjusted into a preset number of sub-images;
the contrast characteristic information acquisition module is used for acquiring target contrast characteristic information of each sub-image;
a contrast adjustment interval obtaining module, configured to determine, in the gray value of the image to be adjusted, a target gray value corresponding to each piece of target contrast characteristic information;
and the contrast adjusting module is used for taking the target gray value as a gray threshold value, and carrying out contrast adjustment on the image to be adjusted based on the gray threshold value to obtain a target image.
An image contrast adjustment apparatus comprising:
a memory for storing a computer program;
a processor for implementing the steps of the image contrast adjustment method as described in any one of the above when the computer program is executed.
A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out the steps of the image contrast adjustment method as set forth in any one of the above.
The application provides an image contrast adjusting method, which includes the steps that an image to be adjusted is obtained; dividing an image to be adjusted into a preset number of sub-images; acquiring target contrast characteristic information of each sub-image; determining a target gray value corresponding to each target contrast characteristic information in the gray value of the image to be adjusted; and taking the target gray value as a gray threshold, and performing contrast adjustment on the image to be adjusted based on the gray threshold to obtain the target image. In the method, the image to be adjusted is divided into the sub-images, the contrast characteristic information of each sub-image is obtained, and the contrast characteristic information can reflect the contrast information of the sub-image, so that the target gray value corresponding to each target contrast characteristic information is determined in the gray value of the image to be adjusted subsequently, and if the target gray value is taken as the gray threshold value, the gray threshold value can be matched with the contrast information of the image to be adjusted, so that if the contrast adjustment is performed on the image to be adjusted based on the gray threshold value, the contrast adjustment is performed on the image equivalently according to the contrast information of the image, and the adjustment process can be ensured to be adaptive to the image. The image contrast adjusting system, the image contrast adjusting device and the computer-readable storage medium solve the corresponding technical problems.
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In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced below, it is obvious that the drawings in the following description are only embodiments of the present application, and for those skilled in the art, other drawings can be obtained according to the provided drawings without creative efforts.
Fig. 1 is a flowchart of an image contrast adjusting method according to an embodiment of the present disclosure;
FIG. 2 is a schematic diagram of contrast jump;
FIG. 3 is a flow chart of determining a target gray scale value;
FIG. 4 is a sample expression of a first correspondence relationship;
FIG. 5 is a flow chart for determining a target stretch scaling factor;
fig. 6 is a schematic structural diagram of an image contrast adjustment system according to an embodiment of the present disclosure;
fig. 7 is a schematic structural diagram of an image contrast adjusting apparatus according to an embodiment of the present application;
fig. 8 is another schematic structural diagram of an image contrast adjusting apparatus according to an embodiment of the present application.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, 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 application.
Referring to fig. 1, fig. 1 is a flowchart illustrating an image contrast adjusting method according to an embodiment of the present disclosure.
The image contrast adjusting method provided by the embodiment of the application can comprise the following steps:
step S11: and acquiring an image to be adjusted.
In practical application, an image to be adjusted, that is, an image that needs to be subjected to contrast adjustment, may be obtained first, and the type of the image to be adjusted may be determined according to actual needs, for example, the image to be adjusted may be an image taken by a monitoring device, a photo taken by a mobile phone, or the like.
Step S12: the image to be adjusted is divided into a preset number of sub-images.
Step S13: and acquiring target contrast characteristic information of each sub-image.
Step S14: and determining a target gray value corresponding to each target contrast characteristic information in the gray value of the image to be adjusted.
In practical applications, since the contrast information of each image is different, if the contrast adjustment is performed according to the uniform contrast adjustment parameter, the image may have a contrast jump phenomenon, for example, in the debugging process shown in fig. 2, the left image is an image obtained by adjusting the original image by using the contrast adjustment parameter suitable for the image itself, and the right image is an image obtained by adjusting the contrast adjustment parameter unsuitable for the image itself, as can be seen from fig. 2, the contrast adjustment effect is poor, in order to solve this problem, it is considered that the gray level threshold value according to which the adjustment is performed in the contrast adjustment process is equivalent to the contrast of the image being correspondingly divided, so that the present application starts from the angle of the gray level threshold value according to which the adjustment is determined according to the contrast information of the image, and after the image to be adjusted is acquired, the image to be adjusted is divided into the preset number of sub-images, the specific numerical value of the preset number can be determined according to actual needs, for example, the preset number can be 2, 3, and the like; acquiring target contrast characteristic information of each sub-image, wherein the contrast characteristic information is corresponding information capable of reflecting image contrast, and the type of the contrast characteristic information can be determined according to actual needs; and the more the pixel points with high gray value and the pixel points with low gray value in the image are, the higher the contrast of the image is, so that the relation exists between the contrast of the image and the gray value of the image, and therefore, in the gray value of the image to be adjusted, the target gray value corresponding to each target contrast characteristic information is determined, so that the target gray value is adaptive to the contrast of the image.
In a specific application scene, in the process of dividing an image to be adjusted into a preset number of sub-images, the image to be adjusted can be divided into the preset number of sub-images by an image segmentation method based on a threshold value; and the types of thresholds include values that can be determined as median, mean, large law based, bimodal histogram based, iterative based, etc. Assuming that the threshold is the mean value, in the process of dividing the image to be adjusted into the preset number of sub-images by the threshold-based image segmentation method, the mean value of the image needs to be calculated first, then the image composed of pixels with values greater than the mean value is divided into one sub-image, and the image composed of pixels with values less than or equal to the mean value is divided into another sub-image, and the like.
In a specific application scenario, the type of the target contrast characteristic information may include variance, standard deviation, weber contrast, root mean square contrast, and the like, and the type of the contrast characteristic information may be determined according to actual needs. Now, assuming that the type of the contrast characteristic information is a standard deviation, the calculation formula of the contrast characteristic information may be as follows:
wherein μ represents a mean value of the image to be adjusted; m multiplied by N represents the number of pixels of the image to be adjusted; sigmaLRepresenting the standard deviation of a sub-image formed by pixels with values smaller than the mean value of the image to be adjusted; cLRepresenting the number of pixels with values smaller than the mean value of the image to be adjusted; mu.sLRepresenting the mean value of the sub-image formed by the pixels with the values smaller than the mean value of the image to be adjusted; x is the number ofiA value representing the ith pixel; sigmaRThe standard deviation of a sub-image formed by pixels with values larger than or equal to the mean value of the image to be adjusted is represented; cRThe number of pixels with the value larger than or equal to the average value of the image to be adjusted is represented; mu.sRThe mean value of sub-images formed by pixels with values larger than or equal to the mean value of the image to be adjusted is represented; x is the number ofiRepresenting the value of the ith pixel.
Step S105: and taking the target gray value as a gray threshold, and performing contrast adjustment on the image to be adjusted based on the gray threshold to obtain the target image.
In practical application, after the target gray value is determined, the target gray value can be used as a gray threshold, and contrast adjustment is performed on the image to be adjusted based on the gray threshold, so that the target image which accords with the contrast adjustment process and accords with the image is obtained.
The application provides an image contrast adjusting method, which includes the steps that an image to be adjusted is obtained; dividing an image to be adjusted into a preset number of sub-images; acquiring target contrast characteristic information of each sub-image; determining a target gray value corresponding to each target contrast characteristic information in the gray value of the image to be adjusted; and taking the target gray value as a gray threshold, and performing contrast adjustment on the image to be adjusted based on the gray threshold to obtain the target image. In the method, the image to be adjusted is divided into the sub-images, the contrast characteristic information of each sub-image is obtained, and the contrast characteristic information can reflect the contrast information of the sub-image, so that the target gray value corresponding to each target contrast characteristic information is determined in the gray value of the image to be adjusted subsequently, and if the target gray value is taken as the gray threshold value, the gray threshold value can be matched with the contrast information of the image to be adjusted, so that if the contrast adjustment is performed on the image to be adjusted based on the gray threshold value, the contrast adjustment is performed on the image equivalently according to the contrast information of the image, and the adjustment process can be ensured to be adaptive to the image.
Referring to fig. 3, fig. 3 is a flowchart for determining a target gray-level value.
In the method for adjusting image contrast provided in the embodiment of the present application, step S14: in the gray value of the image to be adjusted, determining the target gray value corresponding to each target contrast characteristic information may specifically be:
step S141: and acquiring a first corresponding relation between the contrast characteristic information and the stretching scale factor.
In practical application, in the process of determining the target gray values corresponding to the target contrast characteristic information in the gray values of the image to be adjusted, a first corresponding relationship between the contrast characteristic information and a stretch scale coefficient may be obtained first, where the stretch scale coefficient is a ratio of the number of target pixels to the total number of pixels of the image, and the target pixels are pixels meeting requirements, and if the target pixels are pixels whose gray values are less than or equal to 100, the stretch scale coefficient is a ratio of the number of pixels whose gray values are less than or equal to 100 to the total number of pixels of the image.
It should be noted that the first corresponding relationship may be flexibly determined according to actual needs, and assuming that the type of the contrast characteristic information is a standard deviation, the expression of the first corresponding relationship may be
Wherein σ represents a standard deviation; y represents the value of the stretch ratio index corresponding to the standard deviation; m represents a preset parameter value; at this time, the pattern of the first correspondence relationship may be as shown in fig. 4.
Step S142: and acquiring a second corresponding relation between the stretching proportion coefficient and the accumulated gray probability density value.
In practical application, after the first corresponding relationship between the contrast characteristic information and the stretch ratio coefficient is obtained, a second corresponding relationship between the stretch ratio coefficient and an accumulated gray probability density value is also required to be obtained, the accumulated gray probability density value is also the sum of the gray probability densities of the target pixel, and the gray probability density is also the proportion of the number of the pixel points of the target gray to the total number of pixels of the image.
In a specific application scenario, the gray level probability density and the cumulative gray level probability density value can be calculated by the following formulas:
wherein, gkRepresenting the kth gray value;
represents a gray value of gkThe number of pixels of (a); p (g)k) Denotes gkThe gray scale probability density of (a); c (g)K) Denotes gkThe cumulative gray scale probability density value of (1).
Step S143: and determining a target stretching proportion coefficient corresponding to each target contrast characteristic information based on the first corresponding relation.
Step S144: and determining the target gray probability density value corresponding to each target stretching proportion coefficient based on the second corresponding relation.
Step S145: determining a target gray level corresponding to the target gray probability density value, and determining a gray value corresponding to the target gray level as a target gray value; the stretching proportion coefficient comprises the ratio of the number of target pixels to the total number of pixels of the image; the accumulated gray probability density value comprises a sum of the gray probability densities of the target pixels; the target pixels include pixels having a gradation value equal to or less than a cutoff gradation value.
In practical applications, after a first corresponding relationship between the contrast characteristic information and the stretch scale coefficient is obtained and a second corresponding relationship between the stretch scale coefficient and the cumulative gray probability density value is obtained, a target stretch scale coefficient corresponding to each target contrast characteristic information can be determined based on the first corresponding relationship, a target gray probability density value corresponding to each target stretch scale coefficient is determined based on the second corresponding relationship, and since most of the basis is the gray level of an image when the gray probability density values are counted, a target gray level corresponding to the target gray probability density value needs to be determined, and then a gray value corresponding to the target gray level is determined as a target gray value.
Referring to fig. 5, fig. 5 is a flow chart for determining a target stretch scaling factor.
In the method for adjusting image contrast provided in the embodiment of the present application, step S143: based on the first corresponding relationship, determining a target stretch scale coefficient corresponding to each target contrast characteristic information, which may specifically be:
step S1431: and determining a median value in the target contrast characteristic information.
Step S1432: and dividing the target contrast characteristic information which is larger than the median into first type contrast characteristic information.
Step S1433: and dividing the target contrast characteristic information which is less than or equal to the median into second type contrast characteristic information.
In practical application, because the gray values of the pixels in the sub-images are different, and the gray values of the whole sub-images are different, for example, the gray values of all the pixels in one sub-image are higher than those of the other sub-image, for the sub-image with the higher whole pixel value, the contrast characteristic information of the sub-image actually reflects the contrast information of the pixel with the higher gray value in the image to be adjusted, and for the sub-image with the lower whole pixel value, the contrast characteristic information of the sub-image actually reflects the contrast information of the pixel with the lower gray value in the image to be adjusted, so if the target stretch scaling factor is determined in the first correspondence in an orderly manner, the value of the target stretch scaling factor of the sub-image with the higher whole pixel value is larger than the real value, and in order to avoid this situation, in the process of determining the target stretch scaling factor corresponding to each target contrast characteristic information based on the first correspondence, the median value in the target contrast characteristic information needs to be determined, the target contrast characteristic information which is greater than the median value is divided into first-class contrast characteristic information, the target contrast characteristic information which is less than or equal to the median value is divided into second-class contrast characteristic information, namely the first-class contrast characteristic information reflects the contrast information of the sub-image with a low overall pixel value, and the second-class contrast characteristic information reflects the contrast information of the sub-image with a high overall pixel value.
Step S1434: and determining a first stretch scale coefficient corresponding to each piece of first-type contrast characteristic information based on the first corresponding relation, and taking the difference value between 1 and the first stretch scale coefficient as a target stretch scale coefficient corresponding to the first-type contrast characteristic information.
Step S1435: and determining a second stretching proportion coefficient corresponding to each second type of contrast characteristic information based on the first corresponding relation, and directly taking the second stretching proportion coefficient as a target stretching proportion coefficient corresponding to the second type of contrast characteristic information.
In practical application, because the stretch scale coefficient corresponding to the contrast characteristic information of the sub-image with a higher overall pixel value is at the tail of the first corresponding relationship, if the target stretch scale coefficient is determined according to the first corresponding relationship in a reverse order, the value of the target stretch scale coefficient of the sub-image with a higher overall pixel value is close to the true value, and the value of the stretch scale coefficient is 1 at the highest, so that the first stretch scale coefficient corresponding to each piece of the first-type contrast characteristic information can be determined based on the first corresponding relationship, and the difference value between 1 and the first stretch scale coefficient is used as the target stretch scale coefficient corresponding to the first-type contrast characteristic information; because the stretch scale coefficient corresponding to the contrast characteristic information of the sub-image with a lower overall pixel value is at the head of the first corresponding relationship, if the target stretch scale coefficient is determined according to the first corresponding relationship in the forward order, the value of the target stretch scale coefficient of the sub-image with a lower overall pixel value can be made to be close to the true value, so that the second stretch scale coefficient corresponding to each second type of contrast characteristic information can be determined based on the first corresponding relationship, and the second stretch scale coefficient is directly used as the target stretch scale coefficient corresponding to the second type of contrast characteristic information.
It should be noted that, when the image to be adjusted is a low-contrast image, the value of the contrast characteristic information of each of the counted sub-images is relatively small, at this time, if the target stretch scale factor is determined according to the method provided in this embodiment, a target stretch scale factor with a large difference is obtained, that is, the difference value of the grayscale threshold is large, so that the grayscale threshold is closer to the grayscale distribution range of the original image, and thus, if the contrast adjustment is performed according to the grayscale threshold, the contrast enhancement degree of the image is not too large, and the problem of overstretching of a low-contrast scene is avoided; similarly, when the image to be adjusted is a high-contrast image, the value of the contrast characteristic information of each counted sub-image is relatively large, at this time, if the target stretch scale coefficient is determined according to the method provided by the embodiment, a target stretch scale coefficient with a large overall value is obtained, that is, the value of the gray threshold is large, so that if contrast adjustment is performed according to the gray threshold, the contrast enhancement degree of the image cannot be too small, the problem of insufficient stretching of a high-contrast scene is avoided, and the processed image has a good effect.
In the image contrast adjusting method provided by the embodiment of the application, in order to facilitate contrast adjustment of an image to be adjusted, in the process of performing contrast adjustment on the image to be adjusted based on a gray threshold, a stretching multiple and a brightness gain value can be determined based on adjacent gray thresholds; determining a first type of pixels with gray values between adjacent gray threshold values in an image to be adjusted; and adjusting the gray value of the first type of pixels based on the stretching multiple and the brightness gain value.
It should be noted that, in the process of adjusting the contrast of the image to be adjusted based on the gray threshold, for the pixel point whose gray value is smaller than the minimum gray threshold, the gray value of the pixel point can be directly set to 0; for the pixel points with the gray values larger than the maximum gray threshold value, the gray values of the pixel points can be directly set to be the maximum gray values in the image to be adjusted, and the like.
In practical applications, in order to further ensure the adjustment effect of the image to be adjusted and ensure the determination efficiency of the stretching factor and the brightness gain value, in the process of determining the stretching factor and the brightness gain value based on the adjacent gray level threshold values, the method may include: determining a stretching multiple and a brightness gain value based on adjacent gray level threshold values through an adjustment coefficient determination formula; the adjustment coefficient determination formula includes:
wherein, a represents the stretching multiple, b represents the brightness gain value; outR、OutLRepresenting a preset gray value; inRA gray threshold value indicating a larger value of the adjacent gray threshold values; inLA gray threshold value representing a smaller value of the adjacent gray threshold values;
correspondingly, in the process of adjusting the gray value of the first type of pixels based on the stretching multiple and the brightness gain value, the gray value of the first type of pixels can be adjusted based on the stretching multiple and the brightness gain value through a contrast adjustment formula;
the contrast adjustment formula includes:
imOut(x,y)＝a*imIn(x,y)+b；
wherein imOut (x, y) represents the gray value after the adjustment of the first type of pixels; imIn (x, y) represents the original gray value of the first type of pixel; and (x, y) represents the position coordinates of the first type of pixels in the image to be adjusted.
In the image contrast adjusting method provided by the embodiment of the application, before an image to be adjusted is divided into a preset number of sub-images, the number of preset gray level thresholds can be acquired; and taking the number of the preset gray threshold values as the preset number. That is, in the present application, the preset number may be determined according to the number of gray level thresholds according to which the actual contrast ratio is adjusted, for example, if the number of gray level thresholds is 2, the preset number is 2, at this time, the number of sub-images is 2, and the number of gray level thresholds that is finally determined is also 2.
Referring to fig. 6, fig. 6 is a schematic structural diagram of an image contrast adjusting system according to an embodiment of the present disclosure.
An image contrast adjustment system provided by an embodiment of the present application may include:
the image acquisition module 11 is used for acquiring an image to be adjusted;
the image dividing module 12 is configured to divide an image to be adjusted into a preset number of sub-images;
a contrast characteristic information obtaining module 13, configured to obtain target contrast characteristic information of each sub-image;
the contrast adjustment interval obtaining module 14 determines a target gray value corresponding to each target contrast characteristic information in the gray values of the image to be adjusted;
and the contrast adjusting module 15 is configured to use the target gray value as a gray threshold, and perform contrast adjustment on the image to be adjusted based on the gray threshold to obtain the target image.
In an image contrast adjustment system provided in an embodiment of the present application, the contrast adjustment interval obtaining module may include:
the first corresponding relation obtaining submodule is used for obtaining a first corresponding relation between the contrast characteristic information and the stretching proportion coefficient;
the second corresponding relation obtaining submodule is used for obtaining a second corresponding relation between the stretching proportion coefficient and the accumulated gray probability density value;
the stretching proportion coefficient determining submodule is used for determining a target stretching proportion coefficient corresponding to each target contrast characteristic information based on the first corresponding relation;
the gray probability density value determination submodule is used for determining target gray probability density values corresponding to the target stretching proportion coefficients based on the second corresponding relation;
the gray value determining submodule is used for determining a target gray level corresponding to the target gray probability density value and determining the gray value corresponding to the target gray level as a target gray value;
the stretching proportion coefficient comprises the ratio of the number of target pixels to the total number of pixels of the image; the accumulated gray probability density value comprises a sum of the gray probability densities of the target pixels; the target pixels include pixels having a gradation value equal to or less than a cutoff gradation value.
In an image contrast adjusting system provided in an embodiment of the present application, the stretch scale factor determining submodule may include:
a median determination unit, configured to determine a median in the target contrast characteristic information;
the first-class contrast characteristic information determining unit is used for dividing the target contrast characteristic information larger than the median into first-class contrast characteristic information;
the second-type contrast characteristic information determining unit is used for dividing the target contrast characteristic information which is less than or equal to the median into second-type contrast characteristic information;
the first stretching proportion coefficient determining unit is used for determining a first stretching proportion coefficient corresponding to each first-class contrast characteristic information based on the first corresponding relation, and taking the difference value between 1 and the first stretching proportion coefficient as a target stretching proportion coefficient corresponding to the first-class contrast characteristic information;
and the second stretching proportion coefficient determining unit is used for determining a second stretching proportion coefficient corresponding to each second type of contrast characteristic information based on the first corresponding relation, and directly taking the second stretching proportion coefficient as a target stretching proportion coefficient corresponding to the second type of contrast characteristic information.
In an image contrast adjusting system provided in an embodiment of the present application, a contrast adjusting module may include:
the adjustment coefficient determining submodule is used for determining a stretching multiple and a brightness gain value based on adjacent gray level threshold values;
the first-class pixel determination submodule is used for determining first-class pixels of which the gray values are positioned between adjacent gray threshold values in the image to be adjusted;
and the gray value adjusting submodule is used for adjusting the gray value of the first type of pixels based on the stretching multiple and the brightness gain value.
In an image contrast adjusting system provided in an embodiment of the present application, the adjustment coefficient determining sub-module may include:
the adjustment coefficient determining unit is used for determining a stretching multiple and a brightness gain value based on adjacent gray level threshold values through an adjustment coefficient determining formula;
the adjustment coefficient determination formula includes:
wherein, a represents the stretching multiple, b represents the brightness gain value; outR、OutLRepresenting a preset gray value; inRA gray threshold value indicating a larger value of the adjacent gray threshold values; inLA gray threshold value representing a smaller value of the adjacent gray threshold values;
the gray value adjustment sub-module may include:
the gray value adjusting unit is used for adjusting the gray value of the first type of pixels based on the stretching multiple and the brightness gain value through a contrast adjusting formula;
the contrast adjustment formula includes:
imOut(x,y)＝a*imIn(x,y)+b；
wherein imOut (x, y) represents the gray value after the adjustment of the first type of pixels; imIn (x, y) represents the original gray value of the first type of pixel; and (x, y) represents the position coordinates of the first type of pixels in the image to be adjusted.
In an image contrast adjusting system provided in an embodiment of the present application, an image dividing module may include:
the image dividing unit is used for dividing the image to be adjusted into a preset number of sub-images based on the image segmentation method of the threshold value;
the types of the threshold values comprise median values, mean values, values determined based on a large law method, values determined based on a histogram bimodal method and values determined based on an iterative method.
In the image contrast adjusting system provided in the embodiment of the present application, the types of the target contrast characteristic information may include a variance, a standard deviation, a weber contrast, and a root mean square contrast.
The image contrast adjusting system provided by the embodiment of the application can further include:
the gray threshold value quantity acquisition module is used for acquiring the quantity of the preset gray threshold values before the image to be adjusted is divided into the subimages with the preset quantity by the image dividing module;
and the number setting module is used for taking the number of the preset gray threshold values as the preset number.
The application also provides an image contrast adjusting device and a computer readable storage medium, which have the corresponding effects of the image contrast adjusting method provided by the embodiment of the application. Referring to fig. 7, fig. 7 is a schematic structural diagram of an image contrast adjusting apparatus according to an embodiment of the present disclosure.
The image contrast adjusting device provided by the embodiment of the application comprises a memory 201 and a processor 202, wherein a computer program is stored in the memory 201, and the processor 202 implements the following steps when executing the computer program:
acquiring an image to be adjusted;
dividing an image to be adjusted into a preset number of sub-images;
acquiring target contrast characteristic information of each sub-image;
determining a target gray value corresponding to each target contrast characteristic information in the gray value of the image to be adjusted;
and taking the target gray value as a gray threshold, and performing contrast adjustment on the image to be adjusted based on the gray threshold to obtain the target image.
The image contrast adjusting device provided by the embodiment of the application comprises a memory 201 and a processor 202, wherein a computer program is stored in the memory 201, and the processor 202 implements the following steps when executing the computer program: acquiring a first corresponding relation between contrast characteristic information and a stretching proportion coefficient; acquiring a second corresponding relation between the stretching proportion coefficient and the accumulated gray probability density value; determining a target stretching proportion coefficient corresponding to each target contrast characteristic information based on the first corresponding relation; determining target gray probability density values corresponding to the target stretching proportion coefficients based on the second corresponding relation; determining a target gray level corresponding to the target gray probability density value, and determining a gray value corresponding to the target gray level as a target gray value; the stretching proportion coefficient comprises the ratio of the number of target pixels to the total number of pixels of the image; the accumulated gray probability density value comprises a sum of the gray probability densities of the target pixels; the target pixels include pixels having a gradation value equal to or less than a cutoff gradation value.
The image contrast adjusting device provided by the embodiment of the application comprises a memory 201 and a processor 202, wherein a computer program is stored in the memory 201, and the processor 202 implements the following steps when executing the computer program: determining a median value in the target contrast characteristic information; dividing the target contrast characteristic information larger than the median into first type contrast characteristic information; dividing the target contrast characteristic information which is less than or equal to the median into second type contrast characteristic information; determining a first stretch scale coefficient corresponding to each first-type contrast characteristic information based on the first corresponding relation, and taking the difference value between 1 and the first stretch scale coefficient as a target stretch scale coefficient corresponding to the first-type contrast characteristic information; and determining a second stretching proportion coefficient corresponding to each second type of contrast characteristic information based on the first corresponding relation, and directly taking the second stretching proportion coefficient as a target stretching proportion coefficient corresponding to the second type of contrast characteristic information.
The image contrast adjusting device provided by the embodiment of the application comprises a memory 201 and a processor 202, wherein a computer program is stored in the memory 201, and the processor 202 implements the following steps when executing the computer program: determining a stretching multiple and a brightness gain value based on adjacent gray level threshold values; determining a first type of pixels with gray values between adjacent gray threshold values in an image to be adjusted; and adjusting the gray value of the first type of pixels based on the stretching multiple and the brightness gain value.
The image contrast adjusting device provided by the embodiment of the application comprises a memory 201 and a processor 202, wherein a computer program is stored in the memory 201, and the processor 202 implements the following steps when executing the computer program: determining a stretching multiple and a brightness gain value based on adjacent gray level threshold values through an adjustment coefficient determination formula;
the adjustment coefficient determination formula includes:
wherein, a represents the stretching multiple, b represents the brightness gain value; outR、OutLRepresenting a preset gray value; inRA gray threshold value indicating a larger value of the adjacent gray threshold values; inLA gray threshold value representing a smaller value of the adjacent gray threshold values;
correspondingly, adjusting the gray value of the first type of pixels based on the stretching multiple and the brightness gain value through a contrast adjusting formula;
the contrast adjustment formula includes:
imOut(x,y)＝a*imIn(x,y)+b；
wherein imOut (x, y) represents the gray value after the adjustment of the first type of pixels; imIn (x, y) represents the original gray value of the first type of pixel; and (x, y) represents the position coordinates of the first type of pixels in the image to be adjusted.
The image contrast adjusting device provided by the embodiment of the application comprises a memory 201 and a processor 202, wherein a computer program is stored in the memory 201, and the processor 202 implements the following steps when executing the computer program: dividing an image to be adjusted into a preset number of sub-images by using an image segmentation method based on a threshold value; the types of the threshold values comprise median values, mean values, values determined based on a large law method, values determined based on a histogram bimodal method and values determined based on an iterative method.
According to the image contrast adjusting device provided by the embodiment of the application, the types of the target contrast characteristic information comprise variance, standard deviation, weber contrast and root mean square contrast.
The image contrast adjusting device provided by the embodiment of the application comprises a memory 201 and a processor 202, wherein a computer program is stored in the memory 201, and the processor 202 implements the following steps when executing the computer program: acquiring the number of preset gray level thresholds before dividing an image to be adjusted into a preset number of sub-images; and taking the number of the preset gray threshold values as the preset number.
Referring to fig. 8, another image contrast adjusting apparatus provided in the embodiment of the present application may further include: an input port 203 connected to the processor 202, for transmitting externally input commands to the processor 202; a display unit 204 connected to the processor 202, for displaying the processing result of the processor 202 to the outside; and a communication module 205 connected to the processor 202 for communicating the image contrast adjusting device with the outside. The display unit 204 may be a display panel, a laser scanning display, or the like; the communication method adopted by the communication module 205 includes, but is not limited to, mobile high definition link technology (HML), Universal Serial Bus (USB), High Definition Multimedia Interface (HDMI), and wireless connection: wireless fidelity technology (WiFi), bluetooth communication technology, bluetooth low energy communication technology, ieee802.11s based communication technology.
A computer-readable storage medium is provided in an embodiment of the present application, in which a computer program is stored, and when the computer program is executed by a processor, the computer program implements the following steps:
acquiring an image to be adjusted;
dividing an image to be adjusted into a preset number of sub-images;
acquiring target contrast characteristic information of each sub-image;
determining a target gray value corresponding to each target contrast characteristic information in the gray value of the image to be adjusted;
and taking the target gray value as a gray threshold, and performing contrast adjustment on the image to be adjusted based on the gray threshold to obtain the target image.
A computer-readable storage medium is provided in an embodiment of the present application, in which a computer program is stored, and when the computer program is executed by a processor, the computer program implements the following steps: acquiring a first corresponding relation between contrast characteristic information and a stretching proportion coefficient; acquiring a second corresponding relation between the stretching proportion coefficient and the accumulated gray probability density value; determining a target stretching proportion coefficient corresponding to each target contrast characteristic information based on the first corresponding relation; determining target gray probability density values corresponding to the target stretching proportion coefficients based on the second corresponding relation; determining a target gray level corresponding to the target gray probability density value, and determining a gray value corresponding to the target gray level as a target gray value; the stretching proportion coefficient comprises the ratio of the number of target pixels to the total number of pixels of the image; the accumulated gray probability density value comprises a sum of the gray probability densities of the target pixels; the target pixels include pixels having a gradation value equal to or less than a cutoff gradation value.
A computer-readable storage medium is provided in an embodiment of the present application, in which a computer program is stored, and when the computer program is executed by a processor, the computer program implements the following steps: determining a median value in the target contrast characteristic information; dividing the target contrast characteristic information larger than the median into first type contrast characteristic information; dividing the target contrast characteristic information which is less than or equal to the median into second type contrast characteristic information; determining a first stretch scale coefficient corresponding to each first-type contrast characteristic information based on the first corresponding relation, and taking the difference value between 1 and the first stretch scale coefficient as a target stretch scale coefficient corresponding to the first-type contrast characteristic information; and determining a second stretching proportion coefficient corresponding to each second type of contrast characteristic information based on the first corresponding relation, and directly taking the second stretching proportion coefficient as a target stretching proportion coefficient corresponding to the second type of contrast characteristic information.
A computer-readable storage medium is provided in an embodiment of the present application, in which a computer program is stored, and when the computer program is executed by a processor, the computer program implements the following steps: determining a stretching multiple and a brightness gain value based on adjacent gray level threshold values; determining a first type of pixels with gray values between adjacent gray threshold values in an image to be adjusted; and adjusting the gray value of the first type of pixels based on the stretching multiple and the brightness gain value.
A computer-readable storage medium is provided in an embodiment of the present application, in which a computer program is stored, and when the computer program is executed by a processor, the computer program implements the following steps: determining a stretching multiple and a brightness gain value based on adjacent gray level threshold values through an adjustment coefficient determination formula;
the adjustment coefficient determination formula includes:
wherein, a represents the stretching multiple, b represents the brightness gain value; outR、OutLRepresenting a preset gray value; inRA gray threshold value indicating a larger value of the adjacent gray threshold values; inLA gray threshold value representing a smaller value of the adjacent gray threshold values;
adjusting the gray value of the first type of pixels based on the stretching multiple and the brightness gain value through a contrast adjustment formula;
the contrast adjustment formula includes:
imOut(x,y)＝a*imIn(x,y)+b；
wherein imOut (x, y) represents the gray value after the adjustment of the first type of pixels; imIn (x, y) represents the original gray value of the first type of pixel; and (x, y) represents the position coordinates of the first type of pixels in the image to be adjusted.
A computer-readable storage medium is provided in an embodiment of the present application, in which a computer program is stored, and when the computer program is executed by a processor, the computer program implements the following steps: dividing an image to be adjusted into a preset number of sub-images by using an image segmentation method based on a threshold value; the types of the threshold values comprise median values, mean values, values determined based on a large law method, values determined based on a histogram bimodal method and values determined based on an iterative method.
In a computer-readable storage medium provided in an embodiment of the present application, the types of target contrast characteristic information include variance, standard deviation, weber contrast, and root mean square contrast.
A computer-readable storage medium is provided in an embodiment of the present application, in which a computer program is stored, and when the computer program is executed by a processor, the computer program implements the following steps: acquiring the number of preset gray level thresholds before dividing an image to be adjusted into a preset number of sub-images; and taking the number of the preset gray threshold values as the preset number.
The computer-readable storage media to which this application relates include Random Access Memory (RAM), memory, Read Only Memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage media known in the art.
For a description of relevant parts in the image contrast adjustment system, the image contrast adjustment device, and the computer-readable storage medium provided in the embodiments of the present application, reference is made to detailed descriptions of corresponding parts in the image contrast adjustment method provided in the embodiments of the present application, and details are not repeated here. In addition, parts of the above technical solutions provided in the embodiments of the present application, which are consistent with the implementation principles of corresponding technical solutions in the prior art, are not described in detail so as to avoid redundant description.
It is further noted that, herein, relational terms such as first and second, and the like may be 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. Also, 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. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (11)
1. An image contrast adjustment method, comprising:
acquiring an image to be adjusted;
dividing the image to be adjusted into a preset number of sub-images;
acquiring target contrast characteristic information of each sub-image;
determining a target gray value corresponding to each target contrast characteristic information in the gray values of the images to be adjusted;
and taking the target gray value as a gray threshold, and carrying out contrast adjustment on the image to be adjusted based on the gray threshold to obtain a target image.
2. The method according to claim 1, wherein the determining a target gray value corresponding to each target contrast characteristic information in the gray values of the image to be adjusted includes:
acquiring a first corresponding relation between contrast characteristic information and a stretching proportion coefficient;
acquiring a second corresponding relation between the stretching proportion coefficient and the accumulated gray probability density value;
determining a target stretching proportion coefficient corresponding to each target contrast characteristic information based on the first corresponding relation;
determining a target gray probability density value corresponding to each target stretching proportion coefficient based on the second corresponding relation;
determining a target gray level corresponding to the target gray probability density value, and determining a gray value corresponding to the target gray level as the target gray value;
wherein the stretching proportion coefficient comprises the ratio of the number of target pixels to the total number of pixels of the image; the cumulative grayscale probability density value comprises a sum of the grayscale probability densities for the target pixel; the target pixels include pixels having a gray value equal to or less than a cutoff gray value.
3. The method according to claim 2, wherein the determining a target stretch scaling factor corresponding to each target contrast characteristic information based on the first corresponding relationship comprises:
determining a median value in the target contrast characteristic information;
dividing the target contrast characteristic information larger than the median into first-class contrast characteristic information;
dividing the target contrast characteristic information which is less than or equal to the median into second-class contrast characteristic information;
determining a first stretching proportion coefficient corresponding to each first-class contrast characteristic information based on the first corresponding relation, and taking a difference value between 1 and the first stretching proportion coefficient as the target stretching proportion coefficient corresponding to the first-class contrast characteristic information;
and determining a second stretching proportion coefficient corresponding to each second type of contrast characteristic information based on the first corresponding relation, and directly taking the second stretching proportion coefficient as the target stretching proportion coefficient corresponding to the second type of contrast characteristic information.
4. The method of claim 1, wherein the performing contrast adjustment on the image to be adjusted based on the grayscale threshold comprises:
determining a stretching multiple and a brightness gain value based on the adjacent gray level threshold values;
determining a first type of pixels with gray values between adjacent gray threshold values in the image to be adjusted;
and adjusting the gray value of the first type of pixels based on the stretching multiple and the brightness gain value.
5. The method of claim 4, wherein determining the stretch factor and the brightness gain value based on the adjacent gray level threshold values comprises:
determining the stretching multiple and the brightness gain value based on the adjacent gray threshold values through an adjustment coefficient determination formula;
the adjustment coefficient determination formula includes:
wherein a represents the stretch ratio and b represents the brightness gain value; outR、OutLRepresenting a preset gray value; inRThe gray threshold value with a larger value in the adjacent gray threshold values is represented; inLThe gray threshold value with a smaller value is represented in the adjacent gray threshold values;
the adjusting the gray value of the first type of pixels based on the stretching multiple and the brightness gain value comprises:
adjusting the gray value of the first type of pixels based on the stretching multiple and the brightness gain value through a contrast adjustment formula;
the contrast adjustment formula includes:
imOut(x,y)＝a*imIn(x,y)+b；
wherein imOut (x, y) represents the gray value after adjustment of the first type of pixels; imIn (x, y) represents the original gray value of the first type of pixel; (x, y) represents the position coordinates of the first type of pixels in the image to be adjusted.
6. The method according to any one of claims 1 to 5, wherein the dividing the image to be adjusted into a preset number of sub-images comprises:
dividing the image to be adjusted into a preset number of sub-images by using an image segmentation method based on a threshold value;
wherein the types of the threshold values comprise a median value, a mean value, a value determined based on a large law method, a value determined based on a histogram doublet method, and a value determined based on an iteration method.
7. The method of claim 6, wherein the type of the target contrast characteristic information comprises variance, standard deviation, weber contrast, and root mean square contrast.
8. The method according to claim 6, wherein before dividing the image to be adjusted into the preset number of sub-images, the method further comprises:
acquiring the number of preset gray level threshold values;
and taking the number of the preset gray threshold values as the preset number.
9. An image contrast adjustment system, comprising:
the image acquisition module is used for acquiring an image to be adjusted;
the image dividing module is used for dividing the image to be adjusted into a preset number of sub-images;
the contrast characteristic information acquisition module is used for acquiring target contrast characteristic information of each sub-image;
a contrast adjustment interval obtaining module, configured to determine, in the gray value of the image to be adjusted, a target gray value corresponding to each piece of target contrast characteristic information;
and the contrast adjusting module is used for taking the target gray value as a gray threshold value, and carrying out contrast adjustment on the image to be adjusted based on the gray threshold value to obtain a target image.
10. An image contrast adjusting apparatus, characterized by comprising:
a memory for storing a computer program;
a processor for implementing the steps of the image contrast adjustment method according to any one of claims 1 to 8 when executing said computer program.
11. A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out the steps of the image contrast adjustment method according to any one of claims 1 to 8.
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| CN115100084A (en) * | 2022-08-26 | 2022-09-23 | 天津市联大通讯发展有限公司 | Intelligent image enhancement camera shooting method for port complex illumination environment |
| CN115760652A (en) * | 2023-01-06 | 2023-03-07 | 荣耀终端有限公司 | Method for expanding dynamic range of image and electronic equipment |
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| CN115100084A (en) * | 2022-08-26 | 2022-09-23 | 天津市联大通讯发展有限公司 | Intelligent image enhancement camera shooting method for port complex illumination environment |
| CN115760652A (en) * | 2023-01-06 | 2023-03-07 | 荣耀终端有限公司 | Method for expanding dynamic range of image and electronic equipment |
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