A camera module lens shading correction index exceeding detection method and system

Abstract

A method and system for detecting excessive lens shading correction indicators in camera modules. The method comprises: Step 1: capturing a RAW image with the camera module; Step 2: invoking a lens shading detection tool to calculate lens shading correction data based on the RAW image and determine whether the lens shading correction data exceeds the standard; and Step 3: saving the lens shading correction result data. This invention, implemented in the C++ computer language within the Windows development environment, checks lens shading correction indicators during finished product production. Compared to similar products, this method saves significant time, manpower, and financial costs across multiple dimensions, while also breaking through years of established production processes and improving production efficiency.

Description

Technical Field

[0001] The present invention relates to the field of image processing technology, and in particular to a method and system for detecting excessive shading correction indicators of a camera module lens. Background Art

[0002] To ensure imaging quality, existing technologies require testing of the lens shading correction results. After the finished product is produced, whether the lens shading indicators exceed the standard is not checked until the next process stage. This can be achieved by placing a camera inside an integrating sphere, connecting a high-definition multimedia interface cable, and observing the preview image on the display screen. This allows for visual inspection to determine if there are any brightness anomalies. However, visual inspection of the lens shading correction results is time-consuming, has limitations, and is unreliable. Summary of the Invention

[0003] In view of the technical defects and drawbacks in the prior art, the embodiments of the present invention provide a method and system for detecting excessive shading correction indicators of a camera module lens, which overcomes or at least partially solves the above problems. The specific solution is as follows:

[0004] As a first aspect of the present invention, a method for detecting excessive shading correction indicators of a camera module lens is provided, the method comprising:

[0005] Step 1: Take a RAW image using the camera module;

[0006] Step 2: Calling a lens shading detection tool to calculate lens shading correction data based on the RAW image, and determining whether the lens shading correction data exceeds a standard;

[0007] Step 3: Save the lens shading correction result data.

[0008] Furthermore, step 2 includes:

[0009] The RAW image is divided into 17*13 image blocks according to the specific requirements of the tool. For each image block, the channel values ​​of the four channels R, Gr, Gb and B are calculated respectively. The calculation formula is as follows:

[0010] R_avg=Measured Red average-Black level;

[0011] Gr_avg=Measured Gr average-Black level;

[0012] Gb_avg=Measured Gb average-Black level;

[0013] B_avg=Measured Blue average-Black level;

[0014] Among them, Measured Red average is the average value of the R channel under the current light source environment, Measured Graverage is the average value of the Gr channel under the current light source environment; Measured Gb average is the average value of the Gb channel under the current light source environment, Measured Blue average is the average value of the B channel under the current light source environment; R_avg is the R channel value calculated under the current light source environment, Gr_avg is the Gr channel value calculated under the current light source environment, Gb_avg is the Gb channel value calculated under the current light source environment, B_avg is the B channel value calculated under the current light source environment, and Black level is a fixed constant;

[0015] From the 17*13 image block, find the maximum values ​​of the four channels R, Gr, Gb and B respectively, and record them as R_max, Gr_max, Gb_max and B_max, where R_max is the maximum R channel value in the 17*13 image block, Gr_max is the maximum Gr channel value in the 17*13 image block, Gb_max is the maximum Gb channel value in the 17*13 image block, and B_max is the maximum B channel value in the 17*13 image block;

[0016] Based on the maximum values ​​of the four channels R, Gr, Gb and B, the lens shading correction data of the four channels R, Gr, Gb and B of each image block are calculated respectively, which are R_sens, Gr_sens, Gb_sens and B_sens respectively. The calculation formula is as follows:

[0017] R_sens=round(1023×R_avg / R_max);

[0018] Gr_sens=round(1023×Gr_avg / Gr_max);

[0019] Gb_sens=round(1023×Gb_avg / Gb_max);

[0020] B_sens=round(1023×B_avg / B_max);

[0021] Among them, round(1023×R_avg / R_max) is the R channel value divided by the maximum value of the R channel, multiplied by 1023, and finally rounded to the integer; round(1023×Gr_avg / Gr_max) is the Gr channel value divided by the maximum value of the Gr channel, multiplied by 1023, and finally rounded to the integer; round(1023×Gb_avg / Gb_max) is the Gb channel value divided by the maximum value of the Gb channel, multiplied by 1023, and finally rounded to the integer; round(1023×B_avg / B_max) is the B channel value divided by the maximum value of the B channel, multiplied by 1023, and finally rounded to the integer;

[0022] It is determined whether the lens shading correction data of the four channels R, Gr, Gb and B of the central image block are equal to 1023. If they are not equal to 1023, it is determined that the lens shading correction data exceeds the standard.

[0023] Furthermore, the method also includes: determining whether the distribution of lens shading correction data of the four channels R, Gr, Gb and B satisfies a cone shape, that is, the lens shading correction data of the four channels R, Gr, Gb and B of the central image block is the largest, and the lens shading correction data of the four channels R, Gr, Gb and B of the image blocks in the surrounding directions decrease in sequence from the central image block. If the distribution of the lens shading correction data satisfies a cone shape, it is determined that the lens shading correction data does not exceed the standard; otherwise, it is determined that the lens shading correction data exceeds the standard.

[0024] Furthermore, in step 2, for each image block, a partial area of ​​the image block is taken and the channel values ​​of the four channels R, Gr, Gb and B of the corresponding area are calculated.

[0025] Furthermore, the expressions of R_max, Gr_max, Gb_max and B_max are as follows:

[0026]

[0027] Among them, Max(R_avg)of 17×13blocks is the maximum value of the R channel in the 17×13 image blocks; Max(Gr_avg)of 17×13blocks is the maximum value of the Gr channel in the 17×13 image blocks; Max(Gb_avg)of 17×13blocks is the maximum value of the Gb channel in the 17×13 image blocks; Max(B_avg)of 17×13 is the maximum value of the B channel in the 17×13 image blocks.

[0028] As a second aspect of the present invention, a camera module lens shading correction index exceeding detection system is provided, the system comprising: a camera module, a shading correction module and a data storage module;

[0029] The camera module is used to capture RAW images;

[0030] The shading correction module is used to call a lens shading detection tool, calculate lens shading correction data based on the RAW image, and determine whether the lens shading correction data exceeds a standard;

[0031] The data storage module is used to store lens shading correction result data.

[0032] Furthermore, the shading correction module is used to call the lens shading detection tool, calculate the lens shading correction data based on the RAW image, and determine whether the lens shading correction data exceeds the standard. Specifically, the RAW image is divided into 17*13 image blocks according to the specific requirements of the tool, and for each image block, the channel values ​​of the four channels R, Gr, Gb and B are calculated respectively. The calculation formula is as follows;

[0033] R_avg=Measured Red average-Black level;

[0034] Gr_avg=Measured Gr average-Black level;

[0035] Gb_avg=Measured Gb average-Black level;

[0036] B_avg=Measured Blue average-Black level;

[0037] Among them, Measured Red average is the average value of the R channel under the current light source environment, Measured Graverage is the average value of the Gr channel under the current light source environment; Measured Gb average is the average value of the Gb channel under the current light source environment, Measured Blue average is the average value of the B channel under the current light source environment; R_avg is the R channel value calculated under the current light source environment, Gr_avg is the Gr channel value calculated under the current light source environment, Gb_avg is the Gb channel value calculated under the current light source environment, B_avg is the B channel value calculated under the current light source environment, and Black level is a fixed constant;

[0038] From the 17*13 image block, find the maximum values ​​of the four channels R, Gr, Gb and B respectively, and record them as R_max, Gr_max, Gb_max and B_max, where R_max is the maximum R channel value in the 17*13 image block, Gr_max is the maximum Gr channel value in the 17*13 image block, Gb_max is the maximum Gb channel value in the 17*13 image block, and B_max is the maximum B channel value in the 17*13 image block;

[0039] Based on the maximum values ​​of the four channels R, Gr, Gb and B, the lens shading correction data of the four channels R, Gr, Gb and B of each image block are calculated respectively, which are R_sens, Gr_sens, Gb_sens and B_sens respectively. The calculation formula is as follows:

[0040] R_Sens=round(1023×R_avg / R_max);

[0041] Gr_sens=round(1023×Gr_avg / Gr_max);

[0042] Gb_sens=round(1023×Gb_avg / Gb_max);

[0043] B_sens=round(1023×B_avg / B_max);

[0044] Among them, round(1023×R_avg / R_max) is the R channel value divided by the maximum value of the R channel, multiplied by 1023, and finally rounded to the integer; round(1023×Gr_avg / Gr_max) is the Gr channel value divided by the maximum value of the Gr channel, multiplied by 1023, and finally rounded to the integer; round(1023×Gb_avg / Gb_max) is the Gb channel value divided by the maximum value of the Gb channel, multiplied by 1023, and finally rounded to the integer; round(1023×B_avg / B_max) is the B channel value divided by the maximum value of the B channel, multiplied by 1023, and finally rounded to the integer;

[0045] It is determined whether the lens shading correction data of the four channels R, Gr, Gb and B of the central image block are equal to 1023. If they are not equal to 1023, it is determined that the lens shading correction data exceeds the standard.

[0046] Furthermore, the shading correction module is also used to determine whether the distribution of lens shading correction data of the four channels R, Gr, Gb and B satisfies a cone shape, that is, the lens shading correction data of the four channels R, Gr, Gb and B of the central image block is the largest, and the lens shading correction data of the four channels R, Gr, Gb and B of the image blocks in the surrounding directions decrease in sequence from the central image block. If the distribution of the lens shading correction data satisfies a cone shape, it is determined that the lens shading correction data does not exceed the standard; otherwise, it is determined that the lens shading correction data exceeds the standard.

[0047] Furthermore, the channel values ​​of the four channels R, Gr, Gb and B are calculated for each image block as follows: for each image block, a partial area of ​​the image block is taken and the channel values ​​of the four channels R, Gr, Gb and B of the corresponding area are calculated.

[0048] Furthermore, the expressions of R_max, Gr_max, Gb_max and B_max are as follows:

[0049]

[0050] Among them, Max(R_avg)of 17×13blocks is the maximum value of the R channel in the 17×13 image blocks; Max(Gr_avg)of 17×13blocks is the maximum value of the Gr channel in the 17×13 image blocks; Max(Gb_avg)of 17×13blocks is the maximum value of the Gb channel in the 17×13 image blocks; Max(B_avg)of 17×13 is the maximum value of the B channel in the 17×13 image blocks.

[0051] The present invention has the following beneficial effects:

[0052] This invention, implemented in the C++ Windows development environment, checks lens shading correction indicators during finished product production. Compared with similar products, it saves significant time, manpower, and financial resources in multiple dimensions. Furthermore, it breaks through the established production process and improves production efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] Figure 1 A flow chart of a method for detecting excessive shading correction indicators of a camera module lens provided by an embodiment of the present invention;

[0054] Figure 2 Schematic diagram of lens shading correction data for the R channel of each image block;

[0055] Figure 3 Schematic diagram of lens shading correction data for the Gr channel of each image block;

[0056] Figure 4Schematic diagram of lens shading correction data for the Gb channel of each image;

[0057] Figure 5 Schematic diagram of lens shading correction data for the B channel of each image block;

[0058] Figure 6 A schematic diagram of a specific process of detecting excessive shading correction indicators of a camera module lens provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0059] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0060] like Figure 1 As shown, as a first embodiment of the present invention, as a first aspect of the present invention, a method for detecting excessive shading correction indicators of a camera module lens is provided, the method comprising:

[0061] Step 1: Take a RAW image using the camera module;

[0062] Step 2: Calling a lens shading detection tool to calculate lens shading correction data based on the RAW image, and determining whether the lens shading correction data exceeds a standard;

[0063] Step 3: Save the lens shading correction result data.

[0064] In step 1, the data format of the RAW image is shown in Table 1 below;

[0065]

[0066] Table 1

[0067] Preferably, step 2 includes:

[0068] The RAW image is divided into 17*13 image blocks according to the specific requirements of the tool. Part of the image block is taken and the channel values ​​of the four channels R, Gr, Gb and B of the corresponding area are calculated. The area taken for each image block is shown in Table 2 below:

[0069] C(0，0) B_T(1,0) B_T(2,0) ... B_T(14,0) B_T(15,0) C(16，0) B_L(0,1) NB(1,1) ... NB(15,1) B_R(16, 1) B_L(0,2) B_R(16,2) ... ... ... ... B_L(0,10) B_R(16, 10) B_L(0,11) NB(1,11) ... NB(15,11) B_R(16, 11) C(0，12) B_B(1,12) B_B(2, 12) ... B_B(14, 12) B_B(15, 12) C(16，12)

[0070] Table 2

[0071] The formula for calculating the channel values ​​of the four channels R, Gr, Gb and B of the corresponding area is as follows;

[0072] R_avg=Measured Red average-Black level;

[0073] Gr_avg=Measured Gr average-Black level;

[0074] Gb_avg=Measured Gb average-Black level;

[0075] B_avg=Measured Blue average-Black level;

[0076] Among them, Measured Red average is the average value of the R channel under the current light source environment, Measured Graverage is the average value of the Gr channel under the current light source environment; Measured Gb average is the average value of the Gb channel under the current light source environment, Measured Blue average is the average value of the B channel under the current light source environment; R_avg is the R channel value calculated under the current light source environment, Gr_avg is the Gr channel value calculated under the current light source environment, Gb_avg is the Gb channel value calculated under the current light source environment, B_avg is the B channel value calculated under the current light source environment, and Black level is a fixed constant;

[0077] From the 17*13 image block, find the maximum values ​​of the four channels R, Gr, Gb and B respectively, and record them as R_max, Gr_max, Gb_max and B_max;

[0078] The expressions for R_max, Gr_max, Gb_max, and B_max are as follows:

[0079]

[0080] Among them, Max(R_avg)of 17×13blocks is the maximum value of the R channel in the 17×13 image blocks; Max(Gr_avg)of 17×13blocks is the maximum value of the Gr channel in the 17×13 image blocks; Max(Gb_avg)of 17×13blocks is the maximum value of the Gb channel in the 17×13 image blocks; Max(B_avg)of 17×13 is the maximum value of the B channel in the 17×13 image blocks.

[0081] Based on the maximum values ​​of the four channels R, Gr, Gb and B, the lens shading correction data of the four channels R, Gr, Gb and B of each image block are calculated respectively, which are R_sens, Gr_sens, Gb_sens and B_sens respectively. The calculation formula is as follows:

[0082] R_sens=round(1023×R_avg / R_max);

[0083] Gr_sens=round(1023×Gr_avg / Gr_max);

[0084] Gb_sens=round(1023×Gb_avg / Gb_max);

[0085] B_sens=round(1023×B_avg / B_max);

[0086] Among them, round(1023×R_avg / R_max) is the R channel value divided by the maximum value of the R channel, multiplied by 1023, and finally rounded to the integer; round(1023×Gr_avg / Gr_max) is the Gr channel value divided by the maximum value of the Gr channel, multiplied by 1023, and finally rounded to the integer; round(1023×Gb_avg / Gb_max) is the Gb channel value divided by the maximum value of the Gb channel, multiplied by 1023, and finally rounded to the integer; round(1023×B_avg / B_max) is the B channel value divided by the maximum value of the B channel, multiplied by 1023, and finally rounded to the integer;

[0087] It is determined whether the lens shading correction data of the four channels R, Gr, Gb and B of the central image block are equal to 1023. If they are not equal to 1023, it is determined that the lens shading correction data exceeds the standard.

[0088] Determine whether the distribution of the lens shading correction data of the four channels R, Gr, Gb and B satisfies a cone shape, that is, the lens shading correction data of the four channels R, Gr, Gb and B of the central image block is the largest, and the lens shading correction data of the four channels R, Gr, Gb and B of the image blocks from the central image block to the surrounding directions decreases in sequence. If the distribution of the lens shading correction data satisfies a cone shape, it is determined that the lens shading correction data does not exceed the standard; otherwise, it is determined that the lens shading correction data exceeds the standard.

[0089] The lens shading correction data of each image block is shown in 2-5.

[0090] Preferably, the lens shadow detection tool includes four files: Capture_MTK.raw, eeprom_slim.txt, result.txt and msvcp100d.dll. Before lens shadow detection, the system needs to determine whether the four files Capture_MTK.raw, eeprom_slim.txt, result.txt and msvcp100d.dll exist. If they exist, the corresponding files are deleted and the four files Capture_MTK.raw, eeprom_slim.txt, result.txt and msvcp100d.dll are regenerated when the lens shadow detection tool is called to perform lens shadow detection. The specific process is as follows: Figure 6 shown.

[0091] The present invention is implemented in the C++ computer language in the Windows development environment to check the lens shading correction index during the finished product production process. Compared with similar products, it saves a lot of time, manpower, financial resources and other multi-dimensional costs, and breaks through the production process and production efficiency formed over the years.

[0092] As a second embodiment of the present invention, a camera module lens shading correction index exceeding detection system is provided, the system comprising: a camera module, a shading correction module and a data storage module;

[0093] The camera module is used to capture RAW images;

[0094] The shading correction module is used to call a lens shading detection tool, calculate lens shading correction data based on the RAW image, and determine whether the lens shading correction data exceeds a standard;

[0095] The data storage module is used to store lens shading correction result data.

[0096] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for detecting excessive shading correction index of a camera module lens, characterized in that: The method comprises: Step 1: Take a RAW image using the camera module; Step 2: Calling a lens shading detection tool to calculate lens shading correction data based on the RAW image, and determining whether the lens shading correction data exceeds a standard; Step 3, saving the lens shading correction result data; Wherein, step 2 includes: The RAW image is divided into 17*13 image blocks according to the specific requirements of the tool. For each image block, the channel values ​​of the four channels R, Gr, Gb and B are calculated respectively. The calculation formula is as follows: R_avg=Measured Red average-Blacklevel; Gr_avg=MeasuredGraverage-Blacklevel; Gb_avg=Measured Gb average-Black level; B_avg=MeasuredBlueaverage-Blacklevel; Among them, Measured Red average is the average value of the R channel under the current light source environment, Measured Graverage is the average value of the Gr channel under the current light source environment; Measured Gb average is the average value of the Gb channel under the current light source environment, Measured Blue average is the average value of the B channel under the current light source environment; R_avg is the R channel value calculated under the current light source environment, Gr_avg is the Gr channel value calculated under the current light source environment, Gb_avg is the Gb channel value calculated under the current light source environment, B_avg is the B channel value calculated under the current light source environment, and Black level is a fixed constant; From the 17*13 image block, find the maximum values ​​of the four channels R, Gr, Gb and B respectively, and record them as R_max, Gr_max, Gb_max and B_max; Based on the maximum values ​​of the four channels R, Gr, Gb and B, the lens shading correction data of the four channels R, Gr, Gb and B of each image block are calculated respectively, which are R_sens, Gr_sens, Gb_sens and B_sens respectively. The calculation formula is as follows: R_sens=round(10233×R_avg / R_max); Gr_sens=round(1023×Gr_avg / Gr_max); Gb_sens=round(1023×Gb_avg / Gb_max); B_sens=round(1023×B_avg / B_max); Among them, round(1023×R_avg / R_max) is the R channel value divided by the maximum value of the R channel, multiplied by 1023, and finally rounded to the integer; round(1023×Gr_avg / Gr_max) is the Gr channel value divided by the maximum value of the Gr channel, multiplied by 1023, and finally rounded to the integer; round(1023×Gb_avg / Gb_max) is the Gb channel value divided by the maximum value of the Gb channel, multiplied by 1023, and finally rounded to the integer; round(1023×B_avg / B_max) is the B channel value divided by the maximum value of the B channel, multiplied by 1023, and finally rounded to the integer; Determine whether the lens shading correction data of the four channels R, Gr, Gb and B of the central image block are equal to 1023. If not equal to 1023, it is determined that the lens shading correction data exceeds the standard; The method further includes: determining whether the distribution of lens shading correction data of the four channels R, Gr, Gb and B satisfies a cone shape, that is, the lens shading correction data of the four channels R, Gr, Gb and B of the central image block is the largest, and the lens shading correction data of the four channels R, Gr, Gb and B of the image blocks in the surrounding directions decrease in sequence from the central image block. If the distribution of the lens shading correction data satisfies a cone shape, it is determined that the lens shading correction data does not exceed the standard; otherwise, it is determined that the lens shading correction data exceeds the standard.

2. The camera module lens shading correction index exceeding detection method according to claim 1, characterized in that: In step 2, for each image block, a partial area of ​​the image block is taken and the channel values ​​of the four channels R, Gr, Gb and B of the corresponding area are calculated.

3. The camera module lens shading correction index exceeding detection method according to claim 1, characterized in that: The expressions for R_max, Gr_max, Gb_max, and B_max are as follows: Among them, Max(R_avg)of 17×13blocks is the maximum value of the R channel in the 17×13 image blocks; Max(Gr_avg)of 17×13blocks is the maximum value of the Gr channel in the 17×13 image blocks; Max(Gb_avg)of 17×13blocks is the maximum value of the Gb channel in the 17×13 image blocks; Max(B_avg)of 17×13 is the maximum value of the B channel in the 17×13 image blocks.

4. A camera module lens shading correction index exceeding standard detection system, characterized in that: The system includes: a camera module, a shadow correction module and a data storage module; The camera module is used to capture RAW images; The shading correction module is used to call a lens shading detection tool, calculate lens shading correction data based on the RAW image, and determine whether the lens shading correction data exceeds a standard; The data storage module is used to store lens shading correction result data; The shading correction module is used to call the lens shading detection tool, calculate the lens shading correction data based on the RAW image, and determine whether the lens shading correction data exceeds the standard. Specifically, the RAW image is divided into 17*13 image blocks according to the specific requirements of the tool, and for each image block, the channel values ​​of the four channels R, Gr, Gb and B are calculated respectively according to the following calculation formula; R_avg=Measured Red average-Black level; Gr_avg=Measured Gr average-Black level; Gb_avg=Measured Gb average-Black level; B_avg=Measured Blue average-Black level; Among them, Measured Red average is the average value of the R channel under the current light source environment, Measured Graverage is the average value of the Gr channel under the current light source environment; Measured Gb average is the average value of the Gb channel under the current light source environment, Measured Blue average is the average value of the B channel under the current light source environment; R_avg is the R channel value calculated under the current light source environment, Gr_avg is the Gr channel value calculated under the current light source environment, Gb_avg is the Gb channel value calculated under the current light source environment, B_avg is the B channel value calculated under the current light source environment, and Black level is a fixed constant; From the 17*13 image block, find the maximum values ​​of the four channels R, Gr, Gb and B respectively, and record them as R_max, Gr_max, Gb_max and B_max; Based on the maximum values ​​of the four channels R, Gr, Gb and B, the lens shading correction data of the four channels R, Gr, Gb and B of each image block are calculated respectively, which are R_sens, Gr_sens, Gb_sens and B_sens respectively. The calculation formula is as follows: R_sens=round(1023×R_avg / R_max); Gr_sens=round(1023×Gr_avg / Gr_max); Gb_sens=round(1023×Gb_avg / Gb_max); B_sens=round(1023×B_avg / B_max); Among them, round(1023×R_avg / R_max) is the R channel value divided by the maximum value of the R channel, multiplied by 1023, and finally rounded to the integer; round(1023×Gr_avg / Gr_max) is the Gr channel value divided by the maximum value of the Gr channel, multiplied by 1023, and finally rounded to the integer; round(1023×Gb_avg / Gb_max) is the Gb channel value divided by the maximum value of the Gb channel, multiplied by 1023, and finally rounded to the integer; round(1023×B_avg / B_max) is the B channel value divided by the maximum value of the B channel, multiplied by 1023, and finally rounded to the integer; Determine whether the lens shading correction data of the four channels R, Gr, Gb and B of the central image block are equal to 1023. If not equal to 1023, it is determined that the lens shading correction data exceeds the standard; Among them, the shading correction module is also used to: determine whether the distribution of lens shading correction data of the four channels R, Gr, Gb and B satisfies a cone shape, that is, the lens shading correction data of the four channels R, Gr, Gb and B of the central image block is the largest, and the lens shading correction data of the four channels R, Gr, Gb and B of the image blocks in the surrounding directions decrease in sequence from the central image block. If the distribution of the lens shading correction data satisfies a cone shape, it is determined that the lens shading correction data does not exceed the standard; otherwise, it is determined that the lens shading correction data exceeds the standard.

5. The camera module lens shading correction index exceeding standard detection system according to claim 4, characterized in that: The specific method of calculating the channel values ​​of the four channels R, Gr, Gb and B for each image block is as follows: for each image block, a partial area of ​​the image block is taken and the channel values ​​of the four channels R, Gr, Gb and B of the corresponding area are calculated.

6. The camera module lens shading correction index exceeding standard detection system according to claim 4, characterized in that: The expressions for R_max, Gr_max, Gb_max, and B_max are as follows: Among them, Max(R_avg)of 17×13blocks is the maximum value of the R channel in the 17×13 image blocks; Max(Gr_avg)of 17×13blocks is the maximum value of the Gr channel in the 17×13 image blocks; Max(Gb_avg)of 17×13blocks is the maximum value of the Gb channel in the 17×13 image blocks; Max(B_avg)of 17×13 is the maximum value of the B channel in the 17×13 image blocks.

Images