CN114565535A - Image enhancement method and device based on adaptive gradient gamma correction - Google Patents
Image enhancement method and device based on adaptive gradient gamma correction Download PDFInfo
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- 238000004364 calculation method Methods 0.000 claims description 7
- 238000010606 normalization Methods 0.000 claims description 6
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Abstract
The invention discloses an image enhancement method and device based on adaptive gradient gamma correction, wherein the method comprises the following steps: step S1, calculating a log domain gradient histogram of the imageH= [h 0 ,h 1 ,…,h 255 ](ii) a Step S2, calculating an exponential mapping function based on the log domain gradient histogram acquired in step S1; and step S2, based on the exponential mapping function obtained in step S2, performing nonlinear transformation on the image by using a self-adaptive gamma gradient correction algorithm to obtain an enhanced image.
Description
Technical Field
The invention relates to the technical field of image processing, in particular to an image enhancement method and device based on adaptive gradient gamma correction.
Background
Image enhancement is an important pre-processing step in image processing, and can effectively improve image quality. Gamma calibration is one of the most widely applied image enhancement algorithms, and performs exponential transformation on the normalized image gray level to complete image enhancement, thereby achieving the purpose of improving the image brightness distribution. When the transformation index is less than 1, gamma correction can increase the brightness of an image and make the overall brightness of the image more uniform, but the enhanced image contrast becomes low as the image gray level becomes concentrated.
Disclosure of Invention
In order to overcome the defects of the prior art, the present invention provides an image enhancement method and an image enhancement device based on adaptive gradient gamma correction, so as to achieve the purpose of improving the brightness and gradient strength of an image, and further significantly improving the subjective visual effect of the image.
In order to achieve the above and other objects, the present invention provides an image enhancement method based on adaptive gradient gamma correction, comprising the steps of:
step S1, calculating a log domain gradient histogram of the imageH=[h 0 ,h 1 ,…,h 255 ]；
Step S2, calculating an exponential mapping function based on the log domain gradient histogram acquired in step S1;
and step S3, based on the exponential mapping function obtained in step S2, performing nonlinear transformation on the image by using a self-adaptive gamma gradient correction algorithm to obtain an enhanced image.
Preferably, the step S1 further includes:
step S100, setting the initial values of all elements in the histogram H to be 0, and traversing all pixel points of the image;
step S101, for each pixel point, calculating the maximum value and the minimum value of the gray level of the pixel point adjacent to the pixel point in the horizontal direction, and respectively recording the maximum value and the minimum value as the gray level
And
will be the first in the histogram H
Value corresponding to element to 255 th element plus
(ii) a Will be the first in the histogram H
Value corresponding to element to 255 th element minus
；
Step S102, for each pixel point, calculating the maximum value and the minimum value of the gray level of the pixel point adjacent to the pixel point in the vertical direction, and respectively recording the maximum value and the minimum value as the gray level
And
will be the first in the histogram H
Value corresponding to element to 255 th element plus
(ii) a Will be the first in histogram H
Value corresponding to element 255 minus
；
Step S103, after traversing all the pixel points, performing normalization operation on the obtained final histogram H.
Preferably, in step S2, the exponential mapping function is obtained by the following formula:
wherein the parametersmAndnfor controlling the degree of enhancement of the image brightness and gradient, respectively.
Preferably, in step S3, the image is non-linearly transformed according to the obtained exponential mapping function, so as to obtain an enhanced image according to the following formula:
in order to achieve the above object, the present invention further provides an image enhancement device based on adaptive gradient gamma correction, including:
a log domain gradient histogram calculation unit for calculating a log domain gradient histogram of the imageH=[h 0 ,h 1 ,…, h 255 ]；
The exponential mapping function generating unit is used for generating an exponential mapping function based on the log domain gradient histogram acquired by the log domain gradient histogram calculating unit;
and the image enhancement unit is used for carrying out nonlinear transformation on the image by adopting a self-adaptive gamma gradient correction algorithm based on the exponential mapping function acquired by the exponential mapping function generation unit to obtain an enhanced image.
Preferably, the log domain gradient histogram calculation unit is configured to:
setting the initial values of all elements in the histogram H to be 0, and traversing all pixel points of the image;
for each pixel point, calculating the maximum value and the minimum value of the gray level of the pixel point adjacent to the pixel point in the horizontal direction, and respectively recording the maximum value and the minimum value as the gray level of each pixel point
And
will be the first in the histogram H
Value corresponding to element to 255 th element plus
(ii) a Will be the first in the histogram H
Element to 255 thValue corresponding to element minus
；
For each pixel point, calculating the maximum value and the minimum value of the gray level of the pixel point adjacent to the pixel point in the vertical direction, and respectively recording the maximum value and the minimum value as the gray level of each pixel point
And
will be the first in the histogram H
Value corresponding to element to 255 th element plus
(ii) a Will be the first in the histogram H
Value corresponding to element 255 minus
；
And after traversing all the pixel points, carrying out normalization operation on the obtained final histogram H.
Preferably, the exponential mapping function generating unit obtains the exponential mapping function by using the following formula:
wherein the parametersmAndnfor controlling the degree of enhancement of the image brightness and gradient, respectively.
Preferably, the image enhancement unit performs nonlinear transformation on the image to obtain an enhanced image by using the following formula:
compared with the prior art, the image enhancement method and device based on the adaptive gradient gamma correction calculate the logarithm domain gradient histogram of the image, then obtain the exponential mapping function based on the obtained logarithm domain gradient histogram, and perform nonlinear transformation on the image by adopting the adaptive gamma gradient correction algorithm based on the obtained exponential mapping function to obtain the enhanced image, so that the brightness of the image can be effectively improved, and the subjective visual effect of the image can be effectively improved by enhancing the gradient intensity of the image.
Drawings
FIG. 1 is a flowchart illustrating the steps of an image enhancement method based on adaptive gradient gamma correction according to the present invention;
FIG. 2 is a block diagram of an image enhancement apparatus based on adaptive gradient gamma correction according to the present invention;
fig. 3 is a schematic diagram of an image enhancement effect according to an embodiment of the present invention.
Detailed Description
Other advantages and capabilities of the present invention will be readily apparent to those skilled in the art from the present disclosure by describing the embodiments of the present invention with specific embodiments thereof in conjunction with the accompanying drawings. The invention is capable of other and different embodiments and its several details are capable of modification in various other respects, all without departing from the spirit and scope of the present invention.
FIG. 1 is a flowchart illustrating the steps of an image enhancement method based on adaptive gradient gamma correction according to the present invention. As shown in fig. 1, the image enhancement method based on adaptive gradient gamma correction of the present invention includes the following steps:
step S1, calculating a log domain gradient histogram of the imageH=[h 0 ,h 1 ,…,h 255 ]。
In the present invention, it is assumed thatf M×N In order to input an image, the image is, MandNthe number of pixels respectively included in the length and width of the input imageIn particular, step S1 further includes:
and step S100, setting the initial values of all elements of the histogram H to be 0, and traversing all pixel points of the image.
Step S101, for each pixel point, calculating the maximum value and the minimum value of the gray level of the pixel point adjacent to the pixel point in the horizontal direction, and respectively recording the maximum value and the minimum value as the gray level
And
will be the first in the histogram H
Value corresponding to element to 255 th element plus
(ii) a Will be the first in the histogram H
Value corresponding to element 255 minus
；
Step S102, for each pixel point, solving the maximum value and the minimum value of the gray level of the pixel point adjacent to the pixel point in the vertical direction, and respectively recording the maximum value and the minimum value as the gray level
And
will be the first in the histogram H
Value corresponding to element to 255 th element plus
(ii) a Will be the first in histogram H
Value corresponding to element 255 minus
；
Step S103, after traversing all the pixel points, performing normalization operation on the obtained final histogram H:
for ease of understanding and implementation, the following pseudo code for computing an image number domain gradient histogram is given:
step S2, obtaining a histogram of gradient in the logarithmic domain based on the histogram of gradient obtained in step S1H=[h 0 ,h 1 ,…,h 255 ]And calculating an exponential mapping function.
In a specific embodiment of the present invention, the exponential mapping function is calculated as follows:
Wherein the parametersmAndnfor controlling the degree of enhancement of the image brightness and gradient, respectively.
And step S3, based on the exponential mapping function obtained in step S2, performing nonlinear transformation on the image by using a self-adaptive gamma gradient correction algorithm to obtain an enhanced image.
In the specific embodiment of the invention, according to the obtained exponential mapping function, the image is subjected to nonlinear transformation by adopting the following formula to obtain an enhanced image:
It can be seen from the above equation 2 that the index in the adaptive gamma gradient correction algorithm adaptively changes with the gray level, and in addition, the mapping functionγ(l)Parameter (2) ofmAndncontrolling the degree of enhancement of image brightness and gradient, parametersmThe smaller the image, the brighter the image brightness; it can be proven theoretically: parameter(s)nThe larger the image gradient strength. Compared with the traditional gamma correction algorithm, the self-adaptive gamma gradient correction algorithm provided by the invention can effectively improve the brightness of the image and effectively improve the subjective visual effect of the image by enhancing the gradient strength of the image.
FIG. 2 is a block diagram of an image enhancement apparatus based on adaptive gradient gamma correction according to the present invention. As shown in fig. 2, the image enhancement apparatus based on adaptive gradient gamma correction of the present invention includes:
a log domain gradient histogram calculation unit 201 for calculating a log domain gradient histogram of the imageH=[h 0 ,h 1 ,…, h 255 ]。
In the present invention, it is assumed thatf M×N In order to input an image, the image is,MandNthe log domain gradient histogram calculation unit 201 is specifically configured to:
and setting the initial values of all elements of the histogram H as 0, and traversing all pixel points of the image.
For each pixel point, the maximum value and the minimum value of the gray level of the pixel point adjacent to the pixel point in the horizontal direction are calculated and are respectively recorded as
And
in the histogram H, the first
Element to 255 th elementThe value corresponding to the element plus
(ii) a Will be the first in the histogram H
Value corresponding to element 255 minus
；
For each pixel point, the maximum value and the minimum value of the gray level of the pixel point adjacent to the pixel point in the vertical direction are calculated and are respectively recorded as
And
will be the first in the histogram H
Value corresponding to element to 255 th element plus
(ii) a Will be the first in the histogram H
Value corresponding to element 255 minus
；
After traversing all the pixel points, carrying out normalization operation on the obtained final histogram H:
for ease of understanding and implementation, pseudo code for computing the log domain extraction histogram of the image is given below.
An exponential mapping function generation unit 202 for generating a histogram based on the log domain gradient obtained by the log domain gradient histogram calculation unit 201H=[h 0 ,h 1 ,…,h 255 ]And generating an exponential mapping function.
In a specific embodiment of the present invention, the exponential mapping function is obtained by the following formula:
and the image enhancement unit 203 is configured to perform nonlinear transformation on the image by using an adaptive gamma gradient correction algorithm based on the exponential mapping function obtained by the exponential mapping function generation unit 202 to obtain an enhanced image.
In an embodiment of the present invention, the image enhancement unit 203 performs a nonlinear transformation on the image according to the obtained exponential mapping function by using the following formula to obtain an enhanced image:
from the above equation, it can be seen that the index in the adaptive gamma gradient correction algorithm is adaptively changed with the gray level. In addition, a mapping functionγ(l)Parameter (2) ofmAndncontrolling the degree of enhancement of image brightness and gradient, parametersmThe smaller, the brighter the image brightness; it can be proven theoretically: parameter(s)nThe larger the image gradient strength. Compared with the traditional gamma correction algorithm, the self-adaptive gamma gradient correction algorithm provided by the invention can effectively improve the brightness of the image and effectively improve the subjective visual effect of the image by enhancing the gradient strength of the image.
To verify the effectiveness of the present invention, FIG. 3 shows the original image and the use of different parametersmAndncombining corresponding increasesAnd (4) strengthening the back image. The Absolute value of the Mean of Absolute Log-Gradients (MALG) of the images is given above each graph, and it can be seen from the graph that the parameters follownThe image magg becomes larger. When in usem=0.8,n=3In time, the method and the device can improve the brightness and gradient strength of the image, and further improve the subjective visual effect of the image obviously.
The foregoing embodiments are merely illustrative of the principles of the present invention and its efficacy, and are not to be construed as limiting the invention. Modifications and variations can be made to the above-described embodiments by those skilled in the art without departing from the spirit and scope of the present invention. Therefore, the scope of the invention should be determined from the following claims.
Claims (8)
1. An image enhancement method based on adaptive gradient gamma correction comprises the following steps:
step S1, calculating a log domain gradient histogram of the imageH=[h 0 ,h 1 ,…,h 255 ]；
Step S2, calculating an exponential mapping function based on the log domain gradient histogram acquired in step S1;
and step S3, based on the exponential mapping function obtained in step S2, performing nonlinear transformation on the image by using a self-adaptive gamma gradient correction algorithm to obtain an enhanced image.
2. The image enhancement method based on adaptive gradient gamma correction as claimed in claim 1, wherein the step S1 further comprises:
step S100, setting the initial values of all elements in the histogram H to be 0, and traversing all pixel points of the image;
step S101, for each pixel point, calculating the maximum value and the minimum value of the gray level of the pixel point adjacent to the pixel point in the horizontal direction, and respectively recording the maximum value and the minimum value as the gray level
And
will be the first in the histogram H
Value corresponding to element to 255 th element plus
(ii) a Will be the first in the histogram H
Value corresponding to element 255 minus
；
Step S102, for each pixel point, calculating the maximum value and the minimum value of the gray level of the pixel point adjacent to the pixel point in the vertical direction, and respectively recording the maximum value and the minimum value as the gray level
And
will be the first in the histogram H
Value corresponding to element to 255 th element plus
(ii) a Will be the first in the histogram H
Value corresponding to element 255 minus
；
Step S103, after traversing all the pixel points, performing normalization operation on the obtained final histogram H.
3. The image enhancement method based on adaptive gradient gamma correction as claimed in claim 1, wherein in step S2, the exponential mapping function is obtained by the following formula:
wherein the parametersmAndnfor controlling the degree of enhancement of the image brightness and gradient, respectively.
4. The method as claimed in claim 3, wherein in step S3, the image is non-linearly transformed according to the obtained exponential mapping function to obtain the enhanced image by using the following formula:
5. an image enhancement device based on adaptive gradient gamma correction, comprising:
a log domain gradient histogram calculation unit for calculating a log domain gradient histogram of the imageH=[h 0 ,h 1 ,…,h 255 ]；
The exponential mapping function generating unit is used for generating an exponential mapping function based on the log domain gradient histogram acquired by the log domain gradient histogram calculating unit;
and the image enhancement unit is used for carrying out nonlinear transformation on the image by adopting a self-adaptive gamma gradient correction algorithm based on the exponential mapping function acquired by the exponential mapping function generation unit to obtain an enhanced image.
6. An image enhancement device based on adaptive gradient gamma correction as claimed in claim 5, characterized in that the log domain gradient histogram calculation unit is configured to:
setting the initial values of all elements in the histogram H to be 0, and traversing all pixel points of the image;
for each pixel point, calculating the maximum value and the minimum value of the gray level of the pixel point adjacent to the pixel point in the horizontal direction, and respectively recording the maximum value and the minimum value as the gray level of each pixel point
And
will be the first in the histogram H
Value corresponding to element to 255 th element plus
(ii) a Will be the first in the histogram H
Value corresponding to element to 255 th element minus
；
For each pixel point, calculating the maximum value and the minimum value of the gray level of the pixel point adjacent to the pixel point in the vertical direction, and respectively recording the maximum value and the minimum value as the gray level of each pixel point
And
will be the first in the histogram H
Element to 255 thValue corresponding to element plus
(ii) a Will be the first in the histogram H
Value corresponding to element 255 minus
；
And after traversing all the pixel points, carrying out normalization operation on the obtained final histogram H.
7. The image enhancement device according to claim 6, wherein the exponential mapping function generating unit obtains the exponential mapping function by using the following formula:
wherein the parametersmAndnfor controlling the degree of enhancement of the image brightness and gradient, respectively.
8. The image enhancement apparatus according to claim 7, wherein the image enhancement unit performs a non-linear transformation on the image to obtain the enhanced image by using the following formula:
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