CN106952244B - Automatic image brightness adjusting method and device - Google Patents
Automatic image brightness adjusting method and device Download PDFInfo
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- CN106952244B CN106952244B CN201710194067.7A CN201710194067A CN106952244B CN 106952244 B CN106952244 B CN 106952244B CN 201710194067 A CN201710194067 A CN 201710194067A CN 106952244 B CN106952244 B CN 106952244B
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Abstract
The invention provides an automatic image brightness adjusting method and device, comprising the following steps: acquiring a target image to be subjected to brightness adjustment, wherein the target image comprises a plurality of target areas and the corresponding gray values are different; respectively adjusting the weight values of the gray values of the pixels in each target area, which influence the average gray value of the target image, according to the influence of different gray values on the average gray value of the target image, so that the difference of the weight values after the adjustment of at least two target areas is smaller than the difference of the weight values before the adjustment; determining the pixel gray level average value of the target image according to the adjusted weight value and the matched gray level value in each target area; adjusting the brightness of the next frame of target image according to the comparison result of the pixel gray level average value of the target image and the set average gray level threshold value; the effective gray information amount of a small area with large gray gradient in the image is higher by reducing the weight of a larger pixel number statistic value corresponding to the gray value in the target image.
Description
Technical Field
The invention relates to the technical field of image processing, in particular to an automatic image brightness adjusting method and device.
Background
In the 21 st century, with the rapid development of computer technology and the continuous improvement of related theories, digital image processing technology has received extensive attention in many application fields and has achieved significant pioneering achievements. One technique commonly used in digital image processing is automatic adjustment of image brightness.
In the related art, the methods for automatically adjusting the brightness of an image are all based on the average value of the gray levels of the image as an adjustment reference, and the brightness of the whole image is automatically adjusted. However, the adjustment mode has limitations, and aiming at an image with uniform image gray scale distribution, the brightness of the whole image can be well adjusted; for an image with uneven gray distribution, the complex target adjustment of a small area in the image may be worse.
Specifically, for an image with a uniform image gray scale distribution, such as a picture of a snow mountain, the target object is the snow mountain, the target object in the entire image is bright white, and is an area with a low gray scale gradient, the area occupies a large weight value in calculating the average gray scale value, the image gray scale average value of the image is calculated, and the brightness of the entire image is automatically adjusted by using the gray scale average value as an adjustment reference, so that the brightness of the target object can be well adjusted. For an image with uneven image gray distribution, such as a picture of a person climbing a snow mountain, the snow mountain is a background in the whole image, corresponds to bright white, is an area with a lower gray gradient, and occupies a large weight value in calculating an average gray value; the brightness of the artificial target object is low, the artificial target object is a region with high gray gradient, and the weight value of the region in calculating the average gray value is small. Therefore, the average gray scale value of the small region where the target object is located may deviate from the average gray scale value of the image corresponding to the entire image, and at this time, the brightness of the small region where the target object is located is adjusted based on the average gray scale value of the image corresponding to the entire image, so that the adjustment result is poor.
The inventor finds in research that the method for automatically adjusting the brightness of an image in the related art does not consider the problem of uneven image gray distribution of each area in the image, which causes the adjusting method in the related art to have a limitation that it cannot perform a better process for the image with uneven image gray distribution of each area.
Disclosure of Invention
In view of the above, an object of the embodiments of the present invention is to provide a method and an apparatus for automatically adjusting image brightness, which can make the effective gray scale information amount of a small area with a large gray scale gradient in an image higher and make the brightness adjustment result for each target area in the target image better by reducing the weight of a larger statistical value of the number of pixels corresponding to the gray scale value in the target image.
In a first aspect, an embodiment of the present invention provides an automatic adjustment method for image brightness, including:
acquiring a target image to be subjected to brightness adjustment, wherein the target image comprises a plurality of target areas, and the gray values of pixels in the target areas are different;
respectively adjusting the weight values of the average gray value of the target image, which are influenced by the pixel number corresponding to each gray value in each target area according to the influence of the pixel number corresponding to different gray values on the average gray value of the target image, so that the difference of the weight values after the adjustment of at least two target areas is smaller than the difference of the weight values before the adjustment;
determining the pixel gray level average value of the target image according to different gray values in each target area and the number of pixels after the weight adjustment corresponding to each gray value;
and adjusting the brightness of the target image of the next frame according to the comparison result of the pixel gray level average value of the target image and the set average gray level threshold value.
With reference to the first aspect, an embodiment of the present invention provides a first possible implementation manner of the first aspect, where, according to an influence of the number of pixels corresponding to different gray values on an average gray value of the target image, respectively adjusting a weight value of the average gray value of the target image influenced by the number of pixels corresponding to each gray value in each target region, so that a difference between weight values after adjustment of at least two target regions is smaller than a difference between weight values before adjustment of the at least two target regions, includes:
counting the distribution quantity of the pixel points in each target area in a plurality of set gray value ranges respectively to obtain the distribution quantity corresponding to each set gray value range;
according to a set square root coefficient, carrying out square root processing on the distribution quantity corresponding to each set gray value range to obtain adjustment distribution quantities respectively corresponding to each set gray value range; wherein the set square root coefficient satisfies: and the difference of the distribution quantity corresponding to at least two set gray value ranges after the square root processing is smaller than the difference before the adjustment.
With reference to the first possible implementation manner of the first aspect, an embodiment of the present invention provides a second possible implementation manner of the first aspect, where determining a pixel grayscale average value of the target image according to different grayscale values in each target region and the number of pixels with weights corresponding to the grayscale values includes:
determining the integral gray value of the target image according to the adjustment distribution quantity of each set gray value range and the gray value corresponding to each set gray value range;
and determining the average value of the pixel gray scale of the target image according to the integral gray scale value of the target image and the adjustment distribution quantity of each set gray scale value range.
With reference to the first possible implementation manner of the first aspect, an embodiment of the present invention provides a third possible implementation manner of the first aspect, where performing brightness adjustment on a next frame of target image according to a comparison result between a pixel grayscale average value of the target image and a set average grayscale threshold value includes:
comparing the determined pixel gray level average value of the target image with a set average gray level threshold value;
and when the pixel gray level average value is detected not to meet the set average gray level threshold, adjusting the brightness of the next frame of target image according to the difference value between the pixel gray level average value and the set average gray level threshold, so that the pixel gray level average value of the adjusted next frame of target image meets the set average gray level threshold.
With reference to the first aspect, an embodiment of the present invention provides a fourth possible implementation manner of the first aspect, where the method for automatically adjusting brightness of an image further includes:
detecting that a difference result of a difference between the weight values of at least two adjusted target areas and a difference between the weight values of the two adjusted target areas before adjustment meets a preset difference threshold;
when the difference result is smaller than the preset difference threshold value, adjusting and reducing the set root coefficient according to the difference between the difference result and the preset difference threshold value;
and when the difference result is detected to be larger than the preset difference threshold value, adjusting and increasing the set square root coefficient according to the difference between the difference result and the preset difference threshold value.
With reference to the fourth possible implementation manner of the first aspect, the present invention provides a fifth possible implementation manner of the first aspect, wherein the set square root coefficient is greater than or equal to 1.0 and less than or equal to 10.0.
With reference to the first aspect, an embodiment of the present invention provides a sixth possible implementation manner of the first aspect, where the method for automatically adjusting brightness of an image further includes:
acquiring continuous multi-frame target images shot by a camera;
extracting continuous multi-frame target images corresponding to each time period from continuous multi-frame target images according to a plurality of time periods divided in advance;
and automatically adjusting the image brightness of the continuous multi-frame target image corresponding to each time period.
With reference to the sixth possible implementation manner of the first aspect, an embodiment of the present invention provides a seventh possible implementation manner of the first aspect, where automatically adjusting the image brightness of the target image in each time period includes:
acquiring at least one target image in each time period, wherein at least one target image exists behind the target image;
and taking the obtained target image as the target image to be subjected to brightness adjustment.
In a second aspect, an embodiment of the present invention further provides an apparatus for automatically adjusting brightness of an image, including:
the system comprises an acquisition module, a brightness adjustment module and a brightness adjustment module, wherein the acquisition module is used for acquiring a target image to be subjected to brightness adjustment, the target image comprises a plurality of target areas, and the gray values of pixels in the target areas are different;
the adjusting module is used for respectively adjusting the weight values of the average gray value of the target image, which are influenced by the pixel number corresponding to each gray value in each target area according to the influence of the pixel number corresponding to different gray values on the average gray value of the target image, so that the difference between the weight values of at least two target areas after adjustment is smaller than the difference between the weight values of the target areas before adjustment;
the determining module is used for determining the pixel gray level average value of the target image according to different gray values in each target area and the number of pixels after the weight adjustment corresponding to each gray value;
and the brightness adjusting module is used for adjusting the brightness of the next frame of target image according to the comparison result of the pixel gray level average value of the target image and the set average gray level threshold value.
With reference to the second aspect, an embodiment of the present invention provides a first possible implementation manner of the second aspect, where the adjusting module includes:
the statistical unit is used for counting the distribution quantity of the pixel points in each target area in a plurality of set gray value ranges respectively to obtain the distribution quantity corresponding to each set gray value range;
the square root processing unit is used for carrying out square root processing on the distribution quantity corresponding to each set gray value range according to a set square root coefficient to obtain the adjustment distribution quantity respectively corresponding to each set gray value range; wherein the set square root coefficient satisfies: and the difference of the distribution quantity corresponding to at least two set gray value ranges after the square root processing is smaller than the difference before the adjustment.
Compared with the prior art, the method and the device for automatically adjusting the image brightness provided by the embodiment of the invention cannot better process an image with uneven image gray scale distribution in each area, the method and the device adjust the weight value of the average gray scale value of the target image influenced by the number of pixels in each target area according to the influence of the number of pixels corresponding to different gray scale values on the average gray scale value of the target image, so that the difference between the weight values of at least two target areas after adjustment is smaller than the difference between the weight values before adjustment, the weight of a larger statistical value of the number of pixels corresponding to the gray scale value in the target image is reduced, the effective gray scale information quantity of a small area with larger gray scale gradient in the image is higher, and the method and the device are based on the number of pixels with different gray scale values in each target area and the adjusted weight corresponding to each gray scale value, and the brightness of the next frame of target image is adjusted, so that the brightness adjustment result of each target area in the target image is better.
In order to make the aforementioned and other objects, features and advantages of the present invention comprehensible, preferred embodiments accompanied with figures are described in detail below.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained according to the drawings without inventive efforts.
Fig. 1 is a flowchart illustrating an automatic image brightness adjustment method according to an embodiment of the present invention;
FIG. 2 is a flow chart illustrating another method for automatically adjusting brightness of an image according to an embodiment of the present invention;
FIG. 3 is a flow chart of another method for automatically adjusting the brightness of an image according to an embodiment of the present invention;
FIG. 4 is a flow chart illustrating another method for automatically adjusting the brightness of an image according to an embodiment of the present invention;
FIG. 5 is a flow chart illustrating another method for automatically adjusting brightness of an image according to an embodiment of the present invention;
FIG. 6 is a flow chart illustrating another method for automatically adjusting brightness of an image according to an embodiment of the present invention;
fig. 7 is a schematic structural diagram illustrating an apparatus for automatically adjusting image brightness according to an embodiment of the present invention;
fig. 8 is a schematic structural diagram illustrating an adjusting module in an apparatus for automatically adjusting image brightness according to an embodiment of the present invention.
Icon: 10. an acquisition module; 20. an adjustment module; 30. a determination module; 40. a brightness adjustment module; 201. a counting unit; 202. and a square root processing unit.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. The components of embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the present invention, presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the present invention without making any creative effort, shall fall within the protection scope of the present invention.
At present, the average value of the image gray levels is generally used as an adjustment reference for automatic adjustment of the image brightness. The gray scale average calculation may be based on the entire image or may be a partial region in the entire image.
For the image with uniform image gray scale distribution, the existing adjusting mode can better realize the automatic adjustment of the image brightness. However, for an image with uneven gray distribution, for example, a target region with a low gray gradient (i.e. gray level) and a target region with a small region and including a complex target, when calculating the average gray value of the image, the target region with the low gray gradient may occupy a large weight, and the target region with the high gray gradient may occupy a very small weight, and at this time, the average gray value of the target region with the high gray gradient may deviate far from the normal gray value of the entire image, and the effective information amount may be greatly reduced. The target area with lower gray gradient can comprise large-area deserts, lakes, snow mountains and the like; the target area with higher gray scale gradient may include the situation that the brightness of the target such as animals, people, trees and the like on the snow mountain is low, the brightness of the ship, small building or other target in the lake is high, and the brightness of the small target in the desert is high or low.
Therefore, when the brightness adjustment is performed, the brightness adjustment of the target region with a low gray scale gradient is normal, and the brightness adjustment of the other target regions with a high small-area gray scale gradient is not normal.
In an actual image, a large-area target region with a low gray scale gradient is not a region of interest to a user in most cases, and a small-area target region with a high gray scale gradient is often of interest to the user. Under the condition that a person actively selects an area, the aim of adjusting the image with uneven image gray distribution can be achieved by adopting the calculation of the average gray value of the area image, but in the application process of automatically adjusting the image brightness, better adjustment cannot be realized.
Based on the above problem, embodiments of the present invention provide an automatic adjustment method and apparatus for image brightness, which are described below by way of embodiments.
Referring to a flowchart of an automatic adjustment method of image brightness shown in fig. 1, an embodiment of the present invention provides an automatic adjustment method of image brightness, including the following steps:
s101, obtaining a target image to be subjected to brightness adjustment, wherein the target image comprises a plurality of target areas, and gray values of pixels in the target areas are different.
The target image comprises target areas with low gray gradient and complex target areas with high gray gradient, and the gray values of pixels of the images corresponding to the target areas are different.
S102, respectively adjusting the weight values of the average gray value of the target image influenced by the pixel number corresponding to each gray value in each target area according to the influence of the pixel number corresponding to different gray values on the average gray value of the target image, so that the difference of the weight values after the adjustment of at least two target areas is smaller than the difference of the weight values before the adjustment.
Specifically, the target region with a lower gray gradient has a larger influence on the result of calculating the average gray value of the target image, and conversely, the target region with a higher gray gradient has a smaller influence on the result of calculating the average gray value of the target image.
In an actual image, a target region with a low gray scale gradient generally occupies a large range, and a statistical value of the number of pixels corresponding to each gray scale value in the region has a large influence on the calculation result of the gray scale average value of the entire image, whereas a complex target region with a high gray scale gradient generally occupies a small range, and a statistical value of the number of pixels corresponding to each gray scale value in the region has a small influence on the calculation result of the gray scale average value of the entire image. Based on this, the weight value that the number of pixels corresponding to each gray scale value in the target region with a low gray scale gradient in the adjustment target image affects the average gray scale value of the target image becomes relatively small, the weight value that the number of pixels corresponding to each gray scale value in the complex target region with a high gray scale gradient in the adjustment target image affects the average gray scale value of the target image becomes relatively large, and finally the purpose is to reduce the difference between the weight values corresponding to different gray scale statistics values in different target regions. The gray scale statistic is a statistic of the number of pixels corresponding to different gray scale values.
S103, determining the pixel gray level average value of the target image according to different gray values in each target area and the number of pixels after the weight adjustment corresponding to each gray value.
Specifically, the gray scale overall value of the target image is determined according to different gray scale values in each target area and the number of pixels after the weight adjustment corresponding to each gray scale value; and determining the pixel gray level average value of the target image according to the gray level overall value of the target image and the number of the pixels after the weight adjustment corresponding to each gray level value.
And S104, adjusting the brightness of the next frame of target image according to the comparison result of the pixel gray level average value of the target image and the set average gray level threshold value.
In general, the acquired target images are continuous multiple frames, the overlapping degree of the multiple frames of images is high, one target image for brightness adjustment is selected from the multiple target images, the pixel gray average value of the selected target image is determined, then the pixel gray average value of the target image is compared with the set average gray threshold value, and as the current target image is completely shot, the next frame of target image is adjusted according to the comparison result, so that the image brightness of the next frame of target image meets the set requirement. The setting requirement can be that the image brightness meets the requirement that the human eye sensitivity is better when the human eyes normally check, namely the observation degree of the human eyes is matched.
Specifically, if the pixel gray level average value of the target image is smaller than the set average gray level threshold value, the next frame of target image is lightened; if the average value of the pixel gray levels of the target image is larger than the set average gray value threshold value, dimming the next frame of target image; and if the pixel gray level average value of the target image is within the set average gray level threshold value, determining that the image brightness meets the set requirement, and not processing the next frame of image.
In the embodiment of the present invention, the setting of the average gray value threshold may be performed by a user according to an application scene corresponding to the target image and other factors, which is not specifically limited in the embodiment of the present invention. As an alternative, the set average gray value threshold may be a range segment of an interval.
Compared with the prior art, the method for automatically adjusting the image brightness provided by the embodiment of the invention cannot better process an image with uneven image gray scale distribution in each area, the method adjusts the weight value of the average gray scale value of the target image influenced by the number of pixels in each target area according to the influence of the number of pixels corresponding to different gray scale values on the average gray scale value of the target image, so that the difference between the weight values of at least two target areas after adjustment is smaller than the difference between the weight values before adjustment, the method reduces the weight of a larger pixel number statistical value corresponding to the gray scale value in the target image, aims to ensure that the effective gray scale information amount of a small area with larger gray scale gradient in the image is higher, and based on the different gray scale values in each target area and the number of pixels after weight adjustment corresponding to each gray scale value, and the brightness of the next frame of target image is adjusted, so that the brightness adjustment result of each target area in the target image is better.
Further, referring to fig. 2 as an implementation manner, in the step 102, according to the influence of the number of pixels corresponding to different gray values on the average gray value of the target image, respectively adjusting the weight value of the average gray value of the target image influenced by the number of pixels corresponding to each gray value in each target region, so that a difference between the weight values after adjustment of at least two target regions is smaller than a difference between the weight values before adjustment, includes:
s1021, counting the distribution quantity of the pixel points in each target area in a plurality of set gray value ranges respectively to obtain the distribution quantity corresponding to each set gray value range.
As an optional implementation manner, in the embodiment of the present invention, a plurality of set gray value ranges are determined in advance according to the gray value range of the pixels in the target image, specifically, the gray values of the pixels in the target image are arranged in a small-to-large manner, and are respectively represented as a first gray value, a second gray value … …, an nth gray value, and N is a positive integer; then, the origin and the first gray scale value are used as a first set gray scale value range, the first gray scale value and the second gray scale value are used as a second set gray scale value range, and the analogy is repeated to obtain a plurality of set gray scale value ranges.
Then, the distribution quantity of the pixel points in each target area in a plurality of set gray value ranges is counted, so that the distribution quantity is processed at a later period.
As an optional implementation manner, in the embodiment of the present invention, the distribution number of the pixel points in each target region in the range of the plurality of set gray values is counted in a histogram manner. Specifically, a plurality of ranges of the set gray scale values are respectively corresponding to the histograms, and the distribution number of the pixel points in each target region in the ranges of the set gray scale values is represented by the histograms.
S1022, according to the set square root coefficient, square root processing is carried out on the distribution quantity corresponding to each set gray value range, and the adjustment distribution quantity corresponding to each set gray value range is obtained; wherein the set square root coefficient satisfies: and the difference of the distribution quantity corresponding to at least two set gray value ranges after the square root processing is smaller than the difference before the adjustment.
Specifically, the square root processing is evolution processing, and the square root coefficient is a specific power exponent for evolution processing; in the embodiment of the invention, the distribution number corresponding to each set gray value range is subjected to root processing according to the set root coefficient, wherein in one processing of a target image, the root coefficient corresponding to each set gray value range is the same, that is, the distribution number corresponding to each set gray value range is subjected to root processing with equal coefficients, so that the adjusted distribution number respectively corresponding to each set gray value range is obtained and used as the adjusted distribution number.
In the embodiment of the present invention, the set square root coefficient is set by the user according to the application scene corresponding to the target image and other factors, and it needs to satisfy the following condition, that is, the difference between the distribution quantities corresponding to at least two set gray value ranges after the square root processing is smaller than the difference before the adjustment, and the embodiment of the present invention does not specifically limit the difference within the condition.
For the histogram representing the statistical distribution of each gray value, after the square root processing is performed on the statistical distribution quantity of each gray value, a new histogram is obtained, in the new histogram, the abscissa represents the corresponding gray value, and the ordinate represents the square root processing result of the statistical distribution quantity of the pixel point corresponding to each gray value.
In the embodiment of the present invention, the square root processing is performed on the statistical distribution number of the pixel points in each target region in the histogram, and the weight of a certain gray value in each target region in the gray average value is changed, so as to change the calculation result of the average gray value. Further, as the set square root coefficient is smaller, the larger the histogram statistic value of a certain gradation value in the image is, the more rapidly the weight after the square root is reduced.
Further, referring to fig. 3, in the method for automatically adjusting image brightness according to the embodiment of the present invention, in step 103, determining a pixel gray-scale average value of the target image according to different gray-scale values in each target region and the number of pixels after the weight adjustment corresponding to each gray-scale value, includes:
and S1031, determining the gray scale overall value of the target image according to the adjustment distribution quantity of each set gray scale value range and the gray scale value corresponding to each set gray scale value range.
In the embodiment of the present invention, the distribution number represents the weight of the gray-scale value of the pixel in the target region influencing the average gray-scale value of the target image.
And after the adjustment distribution number is obtained, calculating the adjustment distribution number of each set gray value range and the product of the gray values corresponding to each set gray value range, and summing the products of all the set gray value ranges to obtain the gray overall value of the target image.
S1032, determining the pixel gray level average value of the target image according to the gray level overall value of the target image and the adjustment distribution quantity of each set gray level range.
And summing the distribution quantity of each set gray value range adjustment to obtain a summation result, and dividing the summation result by the gray overall value of the target image to obtain the pixel gray average value of the target image.
In combination with steps 1031 to 1032, for the target image, the pixels of the target image are represented in a matrix form, the pixel representation matrix is m rows and N columns, and the gray value of the pixels is N bits; when the set square root coefficient is 1, the calculation formula of the pixel gray level average value of the target image is as follows:
wherein, VagA pixel gray scale average value representing a target image; vgThe term (i, j) denotes a gradation value of a pixel in the ith row and the jth column corresponding to the pixel matrix of the target image.
When the set square root coefficient is more than 1, according to the formula
Determining a pixel gray level average value of the target image; wherein, Vag' represents the mean value of the image gray after square root; sumkRepresenting the number of all pixels in the image having a gray scale value equal to k; k is 1-2N(ii) a N is the gray value of the pixel.
In the embodiment of the invention, the weight with high gray statistic value in the image is reduced through the calculation of the pixel gray average value of the target image after the square root processing, and the average brightness of the image is adjusted according to the square root average gray value, so that the effective gray information content of a small-area with large gray gradient in the image is higher.
Further, referring to fig. 4, in the method for automatically adjusting image brightness according to the embodiment of the present invention, in step 104, according to a comparison result between the pixel gray level average value of the target image and the set average gray level threshold, performing brightness adjustment on the target image of the next frame, including:
and S1041, comparing the determined pixel gray level average value of the target image with a set average gray level threshold value.
As an alternative embodiment, the average gray value threshold is set as a range segment of an interval; and judging whether the pixel gray level average value of the target image is in the range section, if not, comparing the pixel gray level average value of the target image with the minimum value and the maximum value of the range section respectively, and adjusting the brightness of the target image of the next frame according to the comparison result.
And S1042, when the pixel gray level average value is detected not to meet the set average gray level threshold, adjusting the brightness of the next frame of target image according to the difference value between the pixel gray level average value and the set average gray level threshold, so that the pixel gray level average value of the adjusted next frame of target image meets the set average gray level threshold.
Specifically, if the average value of the pixel gray levels of the target image is within the range, it is determined that the brightness of the current target image is normal, and the brightness of the next frame image does not need to be adjusted. If the average value of the pixel gray levels of the target image is not in the range section, brightness adjustment needs to be performed on the next frame of target image, so that the adjusted average value of the pixel gray levels of the next frame of target image is in the range section corresponding to the set average gray value threshold, and the image brightness of the next frame of target image meets the set requirement.
The specific adjusting method comprises the following steps: continuously comparing the pixel gray level average value of the target image with the maximum value in the range section, and if the pixel gray level average value is smaller than the minimum value, brightening the target image of the next frame; and if the maximum value is larger than the maximum value, dimming the next frame of target image.
In the embodiment of the present invention, a specific method for adjusting the brightness of the next frame image includes: calculating an average gray value according to the new gray histogram, and starting to adjust exposure parameters of the camera, such as adjusting the lens aperture size of the camera, the exposure time of the camera, the camera gain and the like, wherein the adjustment of the exposure parameters can adopt a fast approximation method or a slow approximation method;
the fast approximation method is to calculate the exposure parameter size that needs to be adjusted when the next frame of target image reaches normal exposure according to the difference between the pixel average gray value and a set average gray value threshold (the set average gray value threshold is the average gray value interval with normal image brightness), so that the next frame of image can reach normal exposure as soon as possible; the advantages are that the adjusting speed is fast, and the disadvantage is that the brightness adjusting jitter may occur;
the slow approximation method is to realize normal exposure in exposure adjustment of a plurality of continuous target images in a stepping mode according to the difference value between the pixel average gray value and a set average gray value threshold (the set average gray value threshold is an average gray value interval with normal image brightness), and has the advantages that the continuous image brightness adjustment is smooth, the brightness of the visual perception image is changed step by step, and the defect that the adjustment speed is possibly slow;
the embodiment of the invention adopts a mode of combining the advantages of fast adjustment and slow adjustment and selecting proper approaching speed according to the requirement of practical application.
Further, referring to fig. 5, the method for automatically adjusting image brightness according to the embodiment of the present invention further includes:
s201, detecting that a difference value result of a difference between the adjusted weight values of at least two target areas and a difference between the adjusted weight values of the target areas before adjustment meets a preset difference threshold value.
S202, when the difference result is smaller than the preset difference threshold value, adjusting and reducing the set root coefficient according to the difference between the difference result and the preset difference threshold value.
S203, when the difference result is detected to be larger than the preset difference threshold value, adjusting and increasing the set square root coefficient according to the difference between the difference result and the preset difference threshold value.
With reference to steps 201 to 203, in the embodiment of the present invention, whether the target image is a balanced image is determined by adjusting the weight value corresponding to the target region and determining a comparison result of a difference between the weight values of the two regions before and after the adjustment; if the comparison result of the difference between the weighted values of any two target areas in the target image before and after adjustment is smaller than a preset difference threshold value, determining that the target image is a balanced image; and if the comparison result of the difference between the weighted values of any two target areas in the target image before and after adjustment is larger than a preset difference threshold value, determining that the target image is an unbalanced image.
When the target image is determined to be a balanced image, which indicates that the gray value distribution of the pixels in each target area in the target image is relatively uniform, the set square root coefficient is adjusted and reduced according to the difference between the difference result and the preset difference threshold, namely the power exponent for making the square of the distribution quantity corresponding to each gray value is reduced as much as possible. When the target image is determined to be an unbalanced image, the gray value distribution of the pixels of each target area in the target image is uneven and has larger difference, at this time, according to the difference between the difference result and the preset difference threshold, the set square root coefficient is adjusted and increased, namely, the power exponent for making the power on the distribution number of each gray value is increased as much as possible, so that the influence weight of the distribution number corresponding to different gray values on the pixel gray average value of the whole image is adjusted with higher strength.
In the embodiment of the invention, a set square root coefficient (which can be called as square root weight) is represented as t, t is greater than or equal to 1.0 and less than or equal to 10.0, and the smaller the value of t is, the image is an unbalanced image, and the larger the histogram statistic value of a certain gray value is, the more rapidly the weight after the square root is reduced; the smaller the value of t, the closer the image is to the equilibrium image.
Further, referring to fig. 6, the method for automatically adjusting image brightness according to the embodiment of the present invention further includes:
s301, continuous multi-frame target images shot by the camera are acquired.
S302, extracting continuous multi-frame target images corresponding to each time period from continuous multi-frame target images according to a plurality of time periods divided in advance.
In the embodiment of the invention, a camera can shoot continuous multi-frame target images within 1 second, and at the moment, the multi-frame dynamic target images are displayed, and because the eyes of a user have persistence of vision, the multi-frame images seen by the user are actually a static image. The embodiment of the invention aims to meet the set requirement of human eye viewing on the brightness of the target image which looks still for a user.
Therefore, the embodiment of the invention divides the time periods in advance, and each divided time period meets the following conditions: the continuous multi-frame target image included in the time period is a static target image seen by the user.
And S303, automatically adjusting the image brightness of the continuous multi-frame target image corresponding to each time period.
In order to ensure that the brightness of the target image seen by the user meets the requirement, the brightness adjustment processing is performed on the continuous multi-frame target image in each time period in the embodiment of the invention. The specific adjustment processing method comprises the following steps: acquiring at least one target image in each time period, wherein at least one target image exists behind the target image. And taking the obtained target image as the target image to be subjected to brightness adjustment.
Compared with the prior art, the method for automatically adjusting the image brightness provided by the embodiment of the invention cannot better process an image with uneven image gray scale distribution in each area, the method adjusts the weight value of the average gray scale value of the target image influenced by the number of pixels in each target area according to the influence of the number of pixels corresponding to different gray scale values on the average gray scale value of the target image, so that the difference between the weight values of at least two target areas after adjustment is smaller than the difference between the weight values before adjustment, the method reduces the weight of a larger pixel number statistical value corresponding to the gray scale value in the target image, aims to ensure that the effective gray scale information amount of a small area with larger gray scale gradient in the image is higher, and based on the different gray scale values in each target area and the number of pixels after weight adjustment corresponding to each gray scale value, and the brightness of the next frame of target image is adjusted, so that the brightness adjustment result of each target area in the target image is better.
Referring to fig. 7, an apparatus for automatically adjusting image brightness according to an embodiment of the present invention is configured to execute an automatic image brightness adjusting method, where the apparatus includes:
an obtaining module 10, configured to obtain a target image to be subjected to brightness adjustment, where the target image includes a plurality of target areas, and gray values of pixels in the plurality of target areas are different;
an adjusting module 20, configured to respectively adjust a weight value of the target image, which is influenced by the number of pixels corresponding to each gray value in each target region, according to the influence of the number of pixels corresponding to different gray values on the average gray value of the target image, so that a difference between weight values after adjustment of at least two target regions is smaller than a difference between weight values before adjustment;
a determining module 30, configured to determine a pixel grayscale average value of the target image according to different grayscale values in each target region and the number of pixels after the weight adjustment corresponding to each grayscale value;
and the brightness adjusting module 40 is configured to adjust the brightness of the next frame of target image according to the comparison result between the pixel gray level average value of the target image and the set average gray level threshold.
Further, referring to fig. 8, an automatic adjusting apparatus for image brightness according to an embodiment of the present invention, an adjusting module 20, includes:
a counting unit 201, configured to count the number of distribution of the pixel points in each target region in a plurality of ranges of set gray values, respectively, to obtain the number of distribution corresponding to each range of set gray values;
a square root processing unit 202, configured to perform square root processing on the distribution quantity corresponding to each set gray value range according to a set square root coefficient, so as to obtain an adjustment distribution quantity corresponding to each set gray value range; wherein the set square root coefficient satisfies: the difference of the distribution quantity corresponding to at least two set gray value ranges after square root processing is smaller than the difference before adjustment
Further, the apparatus for automatically adjusting image brightness provided by the embodiment of the present invention, the determining module 30, includes:
the first determining unit is used for determining the integral gray level value of the target image according to the adjustment distribution quantity of each set gray level value range and the gray level value corresponding to each set gray level value range;
and the second determining unit is used for determining the pixel gray level average value of the target image according to the gray level overall value of the target image and the adjustment distribution quantity of each set gray level range.
Further, in the automatic adjusting apparatus for image brightness according to the embodiment of the present invention, the brightness adjusting module 40 includes:
the comparison unit is used for comparing the determined pixel gray level average value of the target image with a set average gray level threshold value;
and the brightness adjusting unit is used for adjusting the brightness of the next frame of the target image according to the difference value between the pixel gray average value and the set average gray value threshold when the pixel gray average value is detected not to meet the set average gray value threshold, so that the pixel gray average value of the adjusted next frame of the target image meets the set average gray value threshold.
Further, the automatic adjusting device for image brightness provided by the embodiment of the present invention further includes:
the detection module is used for detecting that a difference result of the difference between the weight values of the at least two target areas after adjustment and the difference between the weight values before adjustment meets a preset difference threshold;
the first adjusting module is used for adjusting and reducing the set square root coefficient according to the difference between the difference result and the preset difference threshold when the difference result is detected to be smaller than the preset difference threshold;
and the second adjusting module is used for adjusting and increasing the set square root coefficient according to the difference between the difference result and the preset difference threshold when the difference result is detected to be larger than the preset difference threshold.
Further, in the apparatus for automatically adjusting image brightness according to the embodiment of the present invention, the set square root coefficient is greater than or equal to 1.0 and less than or equal to 10.0.
Further, the automatic adjusting device for image brightness provided by the embodiment of the present invention further includes:
the acquisition module is used for acquiring continuous multi-frame target images shot by the camera;
the extraction module is used for extracting continuous multi-frame target images corresponding to each time period from continuous multi-frame target images according to a plurality of time periods divided in advance;
and the automatic adjustment module is used for automatically adjusting the image brightness of the continuous multi-frame target image corresponding to each time period.
Further, an automatic adjustment device for image brightness provided by the embodiment of the present invention includes an automatic adjustment module, including:
the acquisition unit is used for acquiring at least one target image in each time period, and at least one target image exists behind the target image;
and the setting unit is used for taking the acquired target image as the target image to be subjected to brightness adjustment.
Compared with the prior art, in which the method for automatically adjusting the image brightness cannot perform better processing on an image with uneven image gray scale distribution in each region, the method for automatically adjusting the image brightness adjusts the weight value of the average gray scale value of the target image influenced by the number of pixels in each target region according to the influence of the number of pixels corresponding to different gray scale values on the average gray scale value of the target image, so that the difference between the weight values of at least two target regions after adjustment is smaller than the difference between the weight values before adjustment, and the method reduces the weight of a larger statistical value of the number of pixels corresponding to the gray scale value in the target image, so as to increase the effective gray scale information amount of a small area region with a larger gray scale gradient in the image, and based on the different gray scale values in each target region and the number of pixels after weight adjustment corresponding to each gray scale value, and the brightness of the next frame of target image is adjusted, so that the brightness adjustment result of each target area in the target image is better.
The automatic adjusting device for image brightness provided by the embodiment of the invention can be specific hardware on the equipment or software or firmware installed on the equipment. The device provided by the embodiment of the present invention has the same implementation principle and technical effect as the method embodiments, and for the sake of brief description, reference may be made to the corresponding contents in the method embodiments without reference to the device embodiments. It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the foregoing systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the embodiments provided in the present invention, it should be understood that the disclosed apparatus and method may be implemented in other ways. The above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units is only one logical division, and there may be other divisions when actually implemented, and for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection of devices or units through some communication interfaces, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments provided by the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit.
The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus once an item is defined in one figure, it need not be further defined and explained in subsequent figures, and moreover, the terms "first", "second", "third", etc. are used merely to distinguish one description from another and are not to be construed as indicating or implying relative importance.
Finally, it should be noted that: the above-mentioned embodiments are only specific embodiments of the present invention, which are used for illustrating the technical solutions of the present invention and not for limiting the same, and the protection scope of the present invention is not limited thereto, although the present invention is described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: any person skilled in the art can modify or easily conceive the technical solutions described in the foregoing embodiments or equivalent substitutes for some technical features within the technical scope of the present disclosure; such modifications, changes or substitutions do not depart from the spirit and scope of the present invention in its spirit and scope. Are intended to be covered by the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the appended claims.
Claims (8)
1. An automatic image brightness adjusting method is characterized by comprising the following steps:
acquiring a target image to be subjected to brightness adjustment, wherein the target image comprises a plurality of target areas, and the gray values of pixels in the target areas are different; the target areas comprise a target area with lower gray gradient and a target area with higher gray gradient, and the area of the target area with lower gray gradient in the target image is larger than that of the target area with higher gray gradient in the target image;
respectively adjusting the weight values of the average gray value of the target image, which are influenced by the pixel number corresponding to each gray value in each target area according to the influence of the pixel number corresponding to different gray values on the average gray value of the target image, so that the difference of the weight values after the adjustment of at least two target areas is smaller than the difference of the weight values before the adjustment;
determining the pixel gray level average value of the target image according to different gray values in each target area and the number of pixels after the weight adjustment corresponding to each gray value;
adjusting the brightness of the next frame of target image according to the comparison result of the pixel gray level average value of the target image and the set average gray level threshold value;
respectively adjusting the weight values of the average gray value of the target image, which are influenced by the number of pixels corresponding to different gray values in each target region according to the influence of the number of pixels corresponding to different gray values on the average gray value of the target image, so that the difference between the weight values of at least two target regions after adjustment is smaller than the difference between the weight values of the target regions before adjustment, including:
counting the distribution quantity of the pixel points in each target area in a plurality of set gray value ranges respectively to obtain the distribution quantity corresponding to each set gray value range;
according to a set square root coefficient, carrying out square root processing on the distribution quantity corresponding to each set gray value range to obtain adjustment distribution quantities respectively corresponding to each set gray value range; wherein the set square root coefficient satisfies: and the difference of the distribution quantity corresponding to at least two set gray value ranges after the square root processing is smaller than the difference before the adjustment.
2. The method of claim 1, wherein determining the average pixel gray level of the target image according to the different gray values in each target region and the number of pixels with weights corresponding to each gray value, comprises:
determining the integral gray value of the target image according to the adjustment distribution quantity of each set gray value range and the gray value corresponding to each set gray value range;
and determining the average value of the pixel gray scale of the target image according to the integral gray scale value of the target image and the adjustment distribution quantity of each set gray scale value range.
3. The method according to claim 1, wherein adjusting the brightness of the target image of the next frame according to the comparison result between the average pixel gray level of the target image and the threshold of the set average gray level value comprises:
comparing the determined pixel gray level average value of the target image with a set average gray level threshold value;
and when the pixel gray level average value is detected not to meet the set average gray level threshold, adjusting the brightness of the next frame of target image according to the difference value between the pixel gray level average value and the set average gray level threshold, so that the pixel gray level average value of the adjusted next frame of target image meets the set average gray level threshold.
4. The method for automatically adjusting the brightness of an image according to claim 1, further comprising:
detecting that a difference result of a difference between the weight values of at least two adjusted target areas and a difference between the weight values of the two adjusted target areas before adjustment meets a preset difference threshold;
when the difference result is smaller than the preset difference threshold value, adjusting and reducing the set root coefficient according to the difference between the difference result and the preset difference threshold value;
and when the difference result is detected to be larger than the preset difference threshold value, adjusting and increasing the set square root coefficient according to the difference between the difference result and the preset difference threshold value.
5. The method according to claim 4, wherein the set square root coefficient is greater than or equal to 1.0 and less than or equal to 10.0.
6. The method for automatically adjusting brightness of an image according to claim 1, further comprising:
acquiring continuous multi-frame target images shot by a camera;
extracting continuous multi-frame target images corresponding to each time period from continuous multi-frame target images according to a plurality of time periods divided in advance;
and automatically adjusting the image brightness of the continuous multi-frame target image corresponding to each time period.
7. The method according to claim 6, wherein the automatically adjusting the image brightness of the target image in each of the time periods comprises:
acquiring at least one target image in each time period, wherein at least one target image exists behind the target image;
and taking the obtained target image as the target image to be subjected to brightness adjustment.
8. An apparatus for automatically adjusting brightness of an image, comprising:
the system comprises an acquisition module, a brightness adjustment module and a brightness adjustment module, wherein the acquisition module is used for acquiring a target image to be subjected to brightness adjustment, the target image comprises a plurality of target areas, and the gray values of pixels in the target areas are different; the target areas comprise a target area with lower gray gradient and a target area with higher gray gradient, and the area of the target area with lower gray gradient in the target image is larger than that of the target area with higher gray gradient in the target image;
the adjusting module is used for respectively adjusting the weight values of the average gray value of the target image, which are influenced by the pixel number corresponding to each gray value in each target area according to the influence of the pixel number corresponding to different gray values on the average gray value of the target image, so that the difference between the weight values of at least two target areas after adjustment is smaller than the difference between the weight values of the target areas before adjustment;
the determining module is used for determining the pixel gray level average value of the target image according to different gray values in each target area and the number of pixels after the weight adjustment corresponding to each gray value;
the brightness adjusting module is used for adjusting the brightness of the next frame of target image according to the comparison result of the pixel gray level average value of the target image and the set average gray level threshold value;
the adjustment module includes:
the statistical unit is used for counting the distribution quantity of the pixel points in each target area in a plurality of set gray value ranges respectively to obtain the distribution quantity corresponding to each set gray value range;
the square root processing unit is used for carrying out square root processing on the distribution quantity corresponding to each set gray value range according to a set square root coefficient to obtain the adjustment distribution quantity respectively corresponding to each set gray value range; wherein the set square root coefficient satisfies: and the difference of the distribution quantity corresponding to at least two set gray value ranges after the square root processing is smaller than the difference before the adjustment.
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