CN115914864A - Adaptive image shading correction method and image shading correction system - Google Patents

Abstract

The present disclosure relates to an adaptive image shading correction method and an image shading correction system. A method and system for adaptive image shading correction are provided. The method comprises the following steps: configuring an image capturing device to obtain a current picture; configuring the image processing circuit to receive the current picture, and configuring the processing unit to execute the following steps: dividing a current picture into a plurality of blocks; selecting a plurality of block pairs from the blocks, wherein the block pairs respectively comprise an inner block and an outer block; performing a screening process aiming at the block pairs, and judging whether a brightness condition, a saturation condition, a hue similarity condition and a sharpness similarity condition are met; in response to obtaining a plurality of screened block pairs, calculating a sum similarity threshold according to the hue statistical data, the saturation difference and the brightness difference; the filtered blocks having individual thresholds less than the sum similarity threshold are used to calculate shading compensation values to adjust the current picture.

Description

Adaptive image shading correction method and image shading correction system

Technical Field

The invention relates to a correction method and a correction system, and in particular to an adaptive image shadow correction method and an image shadow correction system.

Background Art

In the imaging module, there is an inevitable physical phenomenon called lens shading, and its causes can be roughly divided into two categories:

One is luminance shading. Since the lens can be regarded as a convex lens and will concentrate most of the light in the central area, resulting in insufficient light in the corners, the natural light attenuation caused by the incident angle (approximated by cos ⁴ θ) will also cause luminance shading.

The second is called color shading. There is an infrared light filter (IR-CutFilter) in the lens module, which is located between the lens and the image sensor. The purpose is to prevent infrared light that is invisible to the human eye from interfering with the sensor. Infrared light filters are mainly divided into absorption type and reflection type.

Specifically, the advantage of reflective infrared filters is that the cut-off region is steeper, which can cut off more infrared light, but the requirement for the incident light angle is its biggest problem and one of the main reasons for color shadows. The advantage of absorption infrared filters is that they are stable and will not cause the cut-off wavelength to shift due to changes in the incident light angle. Cost considerations are the disadvantages of absorption filters.

Due to the differences between different lenses and sensors, the same image shading compensation setting cannot achieve the same performance for every module. Secondly, the phenomenon of "different colors and different spectra" will occur in shading compensation. The image shading compensation required under similar color temperatures is actually different. However, if it is implemented using the current method, misjudgment often occurs.

Summary of the invention

The technical problem to be solved by the present invention is to provide an adaptive image shading correction method and an image shading correction system in view of the deficiencies in the prior art.

In order to solve the above-mentioned technical problems, one of the technical solutions adopted by the present invention is to provide an adaptive image shading correction method, which includes: configuring an image capture device to obtain a current picture; configuring an image processing circuit to receive the current picture, and configuring a processing unit to perform the following steps: dividing the current picture into a plurality of blocks; selecting a plurality of block pairs from the blocks, wherein the block pairs each include an internal block and an external block, the internal block being one of the blocks in the internal area of the current picture, and the external block being one of the blocks in the external area of the current picture; performing a screening process for each of the block pairs, including the following steps: obtaining a brightness difference and a saturation difference of the current block pair; determining whether the brightness difference and the saturation difference satisfy a brightness condition and a saturation condition, respectively; and determining whether the brightness difference and the saturation difference satisfy a brightness condition and a saturation condition, respectively. The brightness condition and the saturation condition are met, and hue statistics of the current block pair are further obtained; it is determined whether the hue statistics meet the hue similarity condition; in response to the determination that the hue statistics meet the hue similarity condition, the sharpness of the current block pair is further compared to determine whether the sharpness similarity condition is met; and in response to the determination that the sharpness similarity condition is met, the current block pair is regarded as a filtered block pair; in response to obtaining a plurality of filtered block pairs, a total similarity threshold is calculated based on the hue statistics, the saturation difference and the brightness difference of each of the filtered blocks; for each of the filtered blocks, whether there is an individual threshold value less than the total similarity threshold value; the filtered blocks having the individual threshold value less than the total similarity threshold are used to calculate the shadow compensation value; and the current picture is adjusted with the shadow compensation value.

In order to solve the above-mentioned technical problems, another technical solution adopted by the present invention is to provide an adaptive image shading correction system, which includes an image capture device and an image processing circuit. The image capture device is configured to obtain the current picture. The image processing circuit receives the current picture and includes a processing unit, which is configured to: divide the current picture into multiple blocks; select multiple block pairs from the blocks, wherein the block pairs each include an internal block and an external block, the internal block is one of the blocks in the internal area of the current picture, and the external block is one of the blocks in the external area of the current picture; perform a screening process for each of the block pairs, including the following steps: obtain the current brightness difference and saturation difference of the block pair; determine whether the brightness difference and the saturation difference meet the brightness condition and the saturation condition respectively; in response to determining that the brightness difference and the saturation difference meet the brightness condition and the saturation condition respectively, further obtain the hue statistics of the current block pair; determine the whether the hue statistical data satisfies a hue similarity condition; in response to determining that the hue statistical data satisfies the hue similarity condition, further comparing the sharpness of the current block pair to determine whether the sharpness similarity condition is satisfied; and in response to determining that the sharpness similarity condition is satisfied, treating the current block pair as a filtered block pair; in response to obtaining a plurality of filtered block pairs, calculating a total similarity threshold based on the hue statistical data, the saturation difference and the brightness difference of each of the filtered blocks; for each of the filtered blocks, determining whether it has an individual threshold value less than the total similarity threshold value; using the filtered blocks having the individual threshold value less than the total similarity threshold value to calculate a shadow compensation value; and adjusting the current frame with the shadow compensation value to generate an adjusted frame.

One of the beneficial effects of the present invention is that the adaptive image shading correction method and image shading correction system provided by the present invention can achieve a better balance between different modules, and can also avoid the shading compensation error caused by "metamerism". Without consuming additional calculation amount and hardware support, the shading compensation is achieved by the statistics of the existing automatic white balance and automatic exposure.

In addition, the adaptive image shading correction method and image shading correction system provided by the present invention can obtain the pairing result most suitable for shadow compensation operation by filtering out the selected pairing blocks and calculating the similarity, and in all the screened pairing blocks, moving average is implemented separately to achieve deviation extreme value elimination, which can avoid excessive offset caused by a single pairing block, while ensuring the stability of the image shading correction method and image shading correction system of the present invention.

In order to further understand the features and technical contents of the present invention, please refer to the following detailed description and drawings of the present invention. However, the drawings provided are only for reference and description and are not used to limit the present invention.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a functional block diagram of an image shading correction system according to an embodiment of the present invention.

FIG. 2 is a flow chart of an image shading correction method according to an embodiment of the present invention.

FIG. 3 is a schematic diagram of a current picture divided into multiple blocks according to an embodiment of the present invention.

FIG. 4 is a schematic diagram of selecting an inner block and an outer block from a current picture as a block pair according to an embodiment of the present invention.

DETAILED DESCRIPTION

The following is an explanation of the implementation methods of the "adaptive image shading correction method and image shading correction system" disclosed in the present invention through specific embodiments. Those skilled in the art can understand the advantages and effects of the present invention from the contents disclosed in this specification. The present invention can be implemented or applied through other different specific embodiments, and the details in this specification can also be modified and changed in various ways based on different viewpoints and applications without departing from the concept of the present invention. In addition, the drawings of the present invention are only simple schematic illustrations and are not depicted in actual size. It is stated in advance. The following embodiments will further explain the relevant technical contents of the present invention in detail, but the disclosed contents are not intended to limit the scope of protection of the present invention. In addition, the term "or" used in this article may include any one or more combinations of the associated listed items depending on the actual situation.

Referring to FIG. 1 , a first embodiment of the present invention provides an adaptive image shading correction system 1, which includes an image capture device 10 and an image processing circuit 12. The image capture device 10 may be, for example, a camera or a video camera, configured to obtain a current frame FM. The image shading correction system 1 may be a handheld device or a similar device (such as a desktop computer or a laptop computer with similar imaging capabilities). It should be noted that the image processing circuit 12, the processing unit 120, the memory 122 and/or other processing circuits may be generally referred to as "image processing circuit" herein. This image processing circuit may be fully or partially embodied as software, firmware, hardware or any combination thereof. In addition, the image processing circuit may be a single processing module contained, or may be fully or partially incorporated into any of the other components within the image shading correction system 1. Alternatively, the image processing circuit 12 may be partially embodied within the image shading correction system 1.

In the image processing circuit 12 of FIG. 1 , the processing unit 120 and/or other data processing circuits are operably coupled to the memory 122 to execute various algorithms for executing the techniques disclosed in the present invention. These algorithms can be executed by the processing unit 120 and/or other processing circuits, associated firmware or software based on certain instructions that can be executed by the processing unit 120 and/or other processing circuits. Any suitable article (including one or more tangible computer-readable media) can be used to store these instructions to at least centrally store these instructions. The article(s) may include (for example) the memory 122. The memory 122 may include any suitable article for storing data and executable instructions, such as a random access memory, a read-only memory, a rewritable flash memory, a hard drive, and an optical disk.

Further reference may be made to Figures 2, 3 and 4, wherein Figure 2 is a flow chart of an image shading correction method according to an embodiment of the present invention, Figure 3 is a schematic diagram of a current picture divided into multiple blocks according to an embodiment of the present invention, and Figure 4 is a schematic diagram of selecting internal blocks and external blocks from the current picture as block pairs according to an embodiment of the present invention.

As shown in FIG2 , the image shading correction method may include the following steps:

Step S200: divide the current frame FM into a plurality of blocks BLK. For example, FIG3 shows that the current frame FM is divided into a plurality of 10×10 blocks BLK, and the sizes of the blocks BLK are equal, but the present invention is not limited thereto, and the sizes and number of the blocks BLK can be changed according to the requirements.

Step S201: Select a plurality of block pairs from the blocks BLK.

In detail, each block pair includes an inner block IB and an outer block OB, wherein the inner block IB is one of the blocks BLK in the inner area IA of the current frame FM, and the outer block OB is one of the blocks BLK in the outer area OA of the current frame. The number of block pairs can be at most the total number of the blocks BLK, and the selection method can be repeated or non-repeated.

In order to accurately restore the image error caused by the lens shading of the image capture device 10, it is necessary to first select the block pairs with reference value. Therefore, step S202 is executed: a screening process is performed for each of the block pairs, including the following steps:

Step S203: Obtain the brightness difference and saturation difference of the current block pair.

In detail, if only the brightness difference of the block pair is considered, it is easy to cause misjudgment, so the saturation difference needs to be considered at the same time. In some embodiments, the brightness average of multiple pixels in the internal block IB and the brightness average of multiple pixels in the external block OB can be calculated first, and then the difference between the two is used as the brightness difference. In this way, it is possible to avoid performing operations at the pixel level to save system operations.

In addition, in this step, the brightness average of the internal block IB or the external block OB is calculated by eliminating the corresponding pixels whose pixel brightness is higher than the brightness threshold. In other words, the effective pixel brightness in the block can be counted by setting the brightness threshold to eliminate overexposed pixels.

On the other hand, the saturation difference of the block pair is the difference between the saturation of the inner block IB and the saturation of the outer block OB.

The saturation of the inner block IB or the outer block OB can be expressed by the following formula (1):

Wherein, Δ=C _max -C _min , S is the saturation, C _max is the RGB maximum value, and C _min is the RGB minimum value, which can be expressed by the following equations (2) and (3) respectively:

C _max =max(R′, G′, B′)...Equation (2);

C _min =min(R′, G′, B′)...Formula (3);

且

in,

and

R is the red coordinate value, G is the green coordinate value, and B is the blue coordinate value.

Step S204: Determine whether the brightness difference and the saturation difference satisfy the brightness condition and the saturation condition respectively. The brightness condition and the saturation condition may be, for example, when the saturation of both the inner and outer blocks is low, it means that both the inner block and the outer block are close to gray. Based on the determination of shadow compensation, even if the brightness difference between the inner block and the outer block is large, they should still be considered to have a high similarity and can be used as a block pair for determining shadow compensation.

In response to determining that the brightness difference does not satisfy the brightness condition, or the saturation difference does not satisfy the saturation condition, the process proceeds to step S213: the screening process for the current block pair is terminated, and the remaining unscreened block pairs may be continuously determined.

In response to determining that the brightness difference and the saturation difference satisfy the brightness condition and the saturation condition respectively, the process proceeds to step S205 : obtaining hue statistics of the current block pair.

Specifically, the hue statistical data may include red gain and green gain, which may be used as a condition for determining whether a block pair has similar hues.

The red gain (R Gain) is the ratio of the average red coordinate value of all pixels in the outer block or the inner block to the average green coordinate value of all pixels, that is, the ratio of the block average red coordinate value to the block average green coordinate value (R/G). It should be noted that the R Gain of the inner block is marked as R/G, and the R Gain of the outer block is marked as R’/G’.

The blue gain (B Gain) is the ratio of the average blue coordinate value of all pixels in the outer block or the inner block to the average green coordinate value of all pixels, that is, the ratio of the block average blue coordinate value to the block average green coordinate value (B/G). It should be noted that the B Gain of the inner block is marked as B/G, and the B Gain of the outer block is marked as B’/G’.

In addition, although red gain and blue gain can be used as conditions for determining whether a block pair has similar hue, since the green coordinate value of the block pair is the key factor, the hue statistics data also includes the ratio of the block average green coordinate value of the inner block of the current block pair to the block average green coordinate value of the outer block. This ratio is used as a green channel ratio to determine and avoid hue channel errors caused by green coordinate values.

Step S206: Determine whether the hue statistical data meets the hue similarity condition.

In this step, the hue similarity condition may be, for example, to determine whether the following formula (4) is satisfied:

0.9<Hue Diff’/Hue Diff<1.1…Formula (4);

Among them, Hue Diff represents the difference between R/G and B/G in the inner block, and Hue Diff' represents the difference between R'/G' and B'/G' in the outer block. The significance lies in that when converting from RGB coordinates to HSV coordinates, the X axis is R/G and the Y axis is B/G. The values of R/G and B/G on the HSV coordinates can be used as reference values for hue and can be used to replace H in HSV.

Therefore, the step of determining whether the hue statistical data satisfies the hue similarity condition may include first determining whether the green channel ratio is within a predetermined hue range, and then comparing the red gain and the blue gain of the inner block and the outer block.

In response to determining that the hue statistical data satisfies the hue similarity condition, the process proceeds to step S207: comparing the sharpness of the current block pair to determine whether the sharpness similarity condition is satisfied.

Specifically, the sharpness of a block pair is calculated to determine the complexity of the image, and in the case of a complex image, calculating the average grayscale value is actually a reference for shadow compensation. Therefore, the present invention can use the sharpness statistic (AF) to give scenes of different complexities, and the corresponding threshold is used as the weight of the block.

Specifically, the ratio of the sharpness of the inner and outer blocks can be used as a parameter for setting the weight, and the ratio is the smaller value divided by the larger value. For example, if the sharpness ratio of the inner block to the outer block is in the range of 0.9 to 1, the weight is set to 1; if the sharpness ratio falls in the range of 0.75 to 0.9, the average value of this interval is taken as the weight, that is, the weight is (0.75+0.9)/2, which is 0.825, and the weights of all block pairs can be calculated in this way.

The step of comparing the sharpness of the current block pair may include performing edge detection Sobel filters on the outer block OB and the inner block IB respectively to generate inner block sharpness and outer block sharpness for comparison.

The sharpness can be expressed by the following formula (5):

The edge detection Sobel filter can be expressed by the following equations (6) and (7):

Here, Image may be an image corresponding to the external block OB and the internal block IB.

Further, the inner block sharpness can be compared with the outer block sharpness to determine whether the sharpness similarity condition is satisfied. For example, the difference between the inner block sharpness and the outer block sharpness can be calculated, and it can be determined whether the difference is within the sharpness range. Alternatively, the ratio of the inner block sharpness to the outer block sharpness can be calculated, and it can be determined whether the ratio is within the ratio set by the sharpness range, for example, the sharpness range can be set between 0.95 and 1.05.

For example, when the ratio of the inner block sharpness to the outer block sharpness is 1, it means that the inner block sharpness is equal to the outer block sharpness and is within the sharpness range, thus satisfying the sharpness similarity condition. Different confidence weights may be given to different intervals in the sharpness range, for example, when it is within the interval of 1 to 1.03, 100% confidence is given, and the confidence weight is 1, when it is within the interval of 1.03 to 1.05, 80% confidence is given, and the confidence weight is 0.8, and so on.

In response to the determination that the sharpness similarity condition is satisfied, the process proceeds to step S208 : the current block pair is regarded as a filtered block pair, which means that the filtering process has been passed.

After obtaining a plurality of filtered block pairs, the red gain and green gain of each pair can be counted, and moving average filtering can be performed to remove deviation extreme values. In this way, excessive offset caused by a single paired block can be avoided, thereby ensuring the stability of the algorithm of the present invention.

Next, after performing the screening process for each block pair to obtain a plurality of screened block pairs, the process proceeds to step S209 : calculating a total similarity threshold value according to the hue statistics, saturation difference, and brightness difference of each of the screened blocks.

Specifically, the total similarity threshold can be set by calculating the Euclidean norm of the filtered block pairs, which can be expressed by the following formula (8):

Among them, RBGain_Diff is the difference in hue (HUE) between the inner block and the outer block in the filtered block pair, Saturation_Diff is the difference in saturation between the inner block and the outer block in the filtered block pair, and Brightness_Diff is the difference in brightness between the inner block and the outer block in the filtered block pair.

For each of the filtered block pairs, proceed to step S210: determine whether they have individual thresholds less than the total similarity threshold. If yes, proceed to step S211, otherwise proceed to step S214, and eliminate the filtered block pairs that do not have individual thresholds less than the total similarity threshold.

In addition, in step S210, it can be further determined whether the weight of the block pair is greater than a predetermined weight value, that is, the weight determined according to the ratio of the inside and outside sharpness as described above. In some embodiments, if the weight is less than 0.5, the block pair is discarded.

In response to having the individual threshold value smaller than the total similarity threshold value, the process proceeds to step S211 : the filtered blocks having the individual threshold value smaller than the total similarity threshold value are used to calculate the shadow compensation value.

In more detail, the shadow compensation value is calculated mainly by calculating the R/G ratio of the inner block and the R’/G’ ratio of the outer block among the filtered block pairs. If the red gain (R Gain) of the outer block is larger, it is considered that the outer block requires a larger R value.

介于0.99至1.01之间。For example, if the value of R'/G' divided by R/G (i.e., the ratio of the R Gain of the inner block to the R Gain of the outer block) is greater than 1, it means that the red coordinate value R of the outer block is insufficient, so the shadow compensation of the R channel will be increased until this ratio

Between 0.99 and 1.01.

It should be noted that when obtaining the last block pair used for reference, ideally a sufficient number of block pairs should be maintained. However, in practical applications, sometimes the number of obtained block pairs may be too small.

Therefore, in order to avoid the situation where the number of block pairs obtained is too small, which would cause compensation errors, another threshold (percentage) can be used to determine the weight, and a buffer can be set up to try to perform shadow compensation. When more block pairs are not found after a certain number of times, shadow compensation is stopped and this is used as the final result.

When calculating the shadow ratio at the end, use the following formula for the R channel and the B channel respectively:

R channel: (internal red gain/external red gain-1)*corresponding weight;

B channel: (internal blue gain/external blue gain-1)*corresponding weight;

The corresponding weights in the above two formulas are determined by the block pair finally taken out.

For example, n is the number of block pairs obtained, N is the total number of block pairs, if n is less than or equal to N*1/4, the corresponding weight is 1, otherwise the corresponding weight is 4*n/N. The above is only an example, and the present invention is not limited to this condition.

Enter step S212: adjust the current frame with the shading compensation value to generate an adjusted frame.

For example, after determining the shadow compensation value, the current image can be adjusted according to a predetermined correction factor. For example, the adjustment values of the center and edge of the image can be different due to multiplication by the predetermined correction factor. The predetermined correction factor can be, for example, as shown in the following formula (9), where x represents the horizontal coordinate of the image, and y represents the correction factor corresponding to the x coordinate:

In addition, it should be noted that since the brightness, saturation, sharpness and hue statistics used in the above process can be obtained from the inherent hardware statistics of the existing image capture device, the adaptive image shading correction method and image shading correction system provided by the present invention do not require additional computing power and do not require dedicated hardware support.

[Beneficial Effects of Embodiments]

One of the beneficial effects of the present invention is that the adaptive image shading correction method and image shading correction system provided by the present invention can achieve a better balance between different modules, and can also avoid the shading compensation error caused by "metamerism". Without consuming additional calculation amount and hardware support, the shading compensation is achieved by the statistics of the existing automatic white balance and automatic exposure.

In addition, the adaptive image shading correction method and image shading correction system provided by the present invention can obtain the pairing result most suitable for shadow compensation operation by filtering out the selected pairing blocks and calculating the similarity, and in all the screened pairing blocks, moving average is implemented separately to achieve deviation extreme value elimination, which can avoid excessive offset caused by a single pairing block, while ensuring the stability of the image shading correction method and image shading correction system of the present invention.

The contents disclosed above are only preferred feasible embodiments of the present invention, and are not intended to limit the scope of the present invention. Therefore, all equivalent technical changes made using the contents of the present invention's specification and drawings are included in the scope of the present invention.

Explanation of symbols

1: Image shading correction system

12: Image processing circuit

120: Processing unit

122: Memory

10: Image capture device

BLK：Block

FM: Current screen

OA: External Area

IA: Internal Area

OB: External Block

IB: Internal Block

Claims (10)

1. An adaptive image shading correction method, comprising:

configuring an image capture device to obtain a current picture;

configuring the image processing circuit to receive the current frame, and configuring the processing unit to perform the following steps:

dividing the current picture into a plurality of blocks;

selecting a plurality of block pairs from the blocks, wherein the block pairs each include an inner block and an outer block, the inner block being one of the blocks in an inner region of the current picture, the outer block being one of the blocks in an outer region of the current picture;

performing a screening process for each of the block pairs, comprising:

obtaining the brightness difference and the saturation difference of the current block pair;

judging whether the brightness difference and the saturation difference respectively meet a brightness condition and a saturation condition;

responding to the judgment that the brightness difference and the saturation difference respectively meet the brightness condition and the saturation condition, and further obtaining current hue statistical data of the block pair;

judging whether the hue statistical data meets the hue similarity condition;

in response to the judgment that the hue statistical data meets the hue similarity condition, further comparing the sharpness of the current block pair to judge whether the hue statistical data meets the sharpness similarity condition; and

in response to determining that the sharpness similarity condition is satisfied, treating the current pair of blocks as a filtered pair of blocks;

in response to obtaining a plurality of pairs of the filtered blocks, calculating a sum similarity threshold based on the hue statistical data, the saturation difference, and the brightness difference for each of the filtered blocks;

determining, for each of the filtered blocks, whether there is an individual threshold that is less than the sum-similarity threshold;

using the filtered blocks having the respective threshold less than the sum similarity threshold to calculate shading compensation values; and

the current frame is adjusted by the shading compensation value to generate a compensated frame.

2. The image shading correction method of claim 1, wherein in the screening process, the luminance difference of the pair of blocks is a difference between a luminance average of a plurality of pixels in the inner block and a luminance average of a plurality of pixels in the outer block.

3. The method of claim 1, wherein the average luminance of the inner or outer block is calculated by eliminating pixels with luminance higher than a luminance threshold from the corresponding pixels.

4. The image shading correction method of claim 1, wherein in the screening process, the saturation difference of the block pair is a difference between the saturation of the inner block and the saturation of the outer block.

5. The image shading correction method of claim 4, wherein the saturation is represented by the following formula:

wherein, Δ = C _max -C _min S is the saturation, C _max Is the maximum value of RGB, C _min For the RGB minimums, they can be represented by the following formulas:

C _max ＝max(R′，G′，B′)；

C _min ＝min(R′，G′，B′)；

wherein,

and->

Wherein, R is a red coordinate value, G is a green coordinate value, and B is a blue coordinate value.

6. The image shading correction method of claim 1, wherein obtaining the hue statistic data of the current pair of blocks comprises:

respectively calculating the red gain and the green gain of the inner block and the outer block of the current block pair, wherein the red gain is the ratio of the average red coordinate value of the blocks to the average green coordinate value of the blocks, and the blue gain is the ratio of the average blue coordinate value of the blocks to the average green coordinate value of the blocks; and

and calculating the ratio of the block average green coordinate value of the inner block and the block average green coordinate value of the outer block of the current block pair as a green channel ratio.

7. The image shading correction method of claim 6, wherein determining whether the hue statistic satisfies the hue similarity condition comprises:

judging whether the green channel ratio is in a preset hue range or not; and

in response to the green channel ratio being within the predetermined hue range, the red and green gains of the inner and outer blocks are compared.

8. The image shading correction method according to claim 6, further comprising:

in response to obtaining a plurality of pairs of the filtered blocks, the red gain and the green gain are respectively counted, and a moving average filtering is performed to eliminate divergence extrema.

9. The method of claim 1, wherein the step of comparing the sharpness of the current pair of blocks further comprises performing an edge detection Sobel filter on the outer block and the inner block of the current pair of blocks respectively to generate inner block sharpness and outer block sharpness for comparison.

10. An adaptive image shading correction system, comprising:

an image capturing device configured to obtain a current frame;

an image processing circuit receiving the current frame and comprising a processing unit configured to perform the steps of:

dividing the current picture into a plurality of blocks;

selecting a plurality of block pairs from the blocks, wherein the block pairs each include an inner block and an outer block, the inner block being one of the blocks in an inner region of the current picture, the outer block being one of the blocks in an outer region of the current picture;

performing a screening process for each of the block pairs, comprising the steps of:

obtaining the brightness difference and the saturation difference of the current block pair;

judging whether the brightness difference and the saturation difference respectively meet a brightness condition and a saturation condition;

responding to the judgment that the brightness difference and the saturation difference respectively meet the brightness condition and the saturation condition, and further obtaining current hue statistical data of the block pair;

judging whether the hue statistical data meets the hue similarity condition or not;

in response to the judgment that the hue statistical data meets the hue similarity condition, further comparing the sharpness of the current block pair to judge whether the hue statistical data meets the sharpness similarity condition; and

in response to determining that the sharpness similarity condition is satisfied, treating the current pair of blocks as a filtered pair of blocks;

in response to obtaining a plurality of pairs of the filtered blocks, calculating a sum similarity threshold according to the hue statistical data, the saturation difference and the brightness difference of each of the filtered blocks;

determining, for each of the filtered blocks, whether there is an individual threshold that is less than the sum-similarity threshold;

using the filtered blocks having the respective threshold less than the sum similarity threshold to calculate shading compensation values; and

the current frame is adjusted by the shading compensation value to generate an adjusted frame.

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