Dark current correction quality detection method and device, electronic equipment and storage medium

Abstract

The present application provides a kind of dark current correction quality detection method, device, electronic equipment and storage medium, method at least includes: obtaining the sampling data of pixel array in each frame;The sampling data of each frame is processed to obtain the initial frame data of corresponding frame;The initial frame data includes initial average, initial maximum and initial minimum;The intermediate data is obtained by processing the initial frame data;The intermediate data includes frame cumulative average, frame comparison after maximum and frame comparison after minimum;Index data is obtained based on the intermediate data;The index data includes correction average based on the frame cumulative average and critical difference based on the frame comparison after maximum and the frame comparison after minimum;According to the index data, judge, and realize the detection of CIS dark current correction quality according to the result of judgment.The present application can be detected automatically in real time, so as to effectively improve product quality classification efficiency.

Description

Technical Field

[0001] This invention relates to the field of measurement technology, and in particular to a method, apparatus, electronic device, and storage medium for detecting dark current correction quality. Background Technology

[0002] Most CMOS image sensors (CIS) use photodiodes based on semiconductor PN junctions as their photosensitive units. A reverse bias voltage is applied across the photodiode, causing it to operate in photoconductive mode. When illuminated, the photodiode can generate a photocurrent proportional to the incident light over a wide range, converting the optical signal into an electrical signal. In addition to the photoelectric effect, the semiconductor material (usually silicon) constituting the photodiode undergoes thermal excitation, causing electrons in the valence band to transition to the conduction band, forming electron-hole pairs. Simultaneously, a dark current is generated under the influence of a reverse bias voltage.

[0003] Dark current ultimately manifests as noise in the image signal. During the image sensor exposure stage, the accumulated charge from dark current occupies storage space that should be occupied by photogenerated charge, reducing the dynamic range of the image sensor. However, during the manufacturing process of CIS (CMOS Image Sensor), the dark current (black level) is directly related to the manufacturing process. Under specific process conditions after manufacturing, the dark current exhibits an exponential relationship with absolute temperature, i.e.:

[0004]

[0005] Among them, E a Let k be the bandgap of the semiconductor, and k be the Boltzmann constant (k = 1.38 constant 10). -23 J / K), where T is the absolute temperature.

[0006] Currently, there are two main approaches to reducing dark current: one is to improve the manufacturing process and structure from the perspective of the pixel array, reduce the absolute value of the dark current of the pixel array, and improve the uniformity of the dark current magnitude of the pixel array; the other is to use various processing methods in the image processing stage to reduce the impact of dark current on image quality.

[0007] In the image processing stage, dark current noise correction technology is often used. Dark current correction has always been a very important aspect of CIS image quality. Currently, the detection method for dark current correction is manual comparison, which requires setting different test conditions and calculating the dark current of a large number of CIS images using multiple frames of data. This is time-consuming and resource-intensive. Summary of the Invention

[0008] In view of the shortcomings of the prior art described above, the purpose of this invention is to provide a method, apparatus, electronic device and storage medium for detecting dark current correction quality, so as to solve the problems of time-consuming, labor-intensive and inefficient manual detection in the prior art.

[0009] To achieve the above and other related objectives, the present invention provides a method for detecting dark current correction quality, performed under dark conditions, and the detection method includes at least the following steps:

[0010] Obtain the sampled data of the pixel array in each frame;

[0011] The sampled data of each frame is processed to obtain the initial frame data of the corresponding frame; the initial frame data includes the initial average value, the initial maximum value, and the initial minimum value;

[0012] The initial frame data is processed to obtain intermediate data; the intermediate data includes the cumulative average value of frames, the maximum value after frame comparison, and the minimum value after frame comparison.

[0013] The indicator data is obtained based on the intermediate data; the indicator data includes the corrected mean value obtained based on the cumulative average value of the frames and the critical difference value obtained based on the maximum value and the minimum value after the frame comparison.

[0014] The judgment is made based on the aforementioned indicator data, and the quality of CIS dark current correction is detected based on the judgment result.

[0015] Preferably, the method for obtaining the initial frame data includes: dividing the sampled data into several blocks, selecting at least one of the blocks for processing to obtain the initial frame data of the corresponding frame.

[0016] Preferably, the sampled data of a frame is averaged to obtain the initial average value corresponding to that frame; and / or, the sampled data of a frame is compared to obtain the initial maximum value and the initial minimum value corresponding to that frame.

[0017] Preferably, the sampled data of each frame is processed according to the color channels to obtain the corresponding initial frame data.

[0018] Preferably, the process of obtaining the index data further includes: comparing the difference between the initial average values ​​corresponding to any two color channels with a first set threshold, and obtaining the index data when the difference between the initial average values ​​corresponding to the color channels is less than the first set threshold.

[0019] Preferably, the method for obtaining the indicator data includes:

[0020] The indicator data is obtained based on the intermediate data and the set conditions. The intermediate data that meets the set conditions is used as the calculation data to obtain the indicator data. The set conditions are: the cumulative average value of the frames is greater than the second set threshold, and / or the difference between the maximum value and the minimum value after frame comparison is greater than the third set threshold.

[0021] Preferably, the OB quality of dark current correction is determined based on the correction mean in the index data; and / or, the stability quality of dark current correction is determined based on the critical difference in the index data, wherein the critical difference is the difference between the maximum value and the minimum value after frame comparison.

[0022] Preferably, the intermediate data is obtained using a frame-by-frame comparison method, which includes the following steps:

[0023] Obtain the initial frame data of the current frame, which includes the initial average value, the initial maximum value, and the initial minimum value of the current frame.

[0024] Obtain the update frame data of the previous frame, wherein the update frame data of the previous frame includes the average update value, the maximum update value, and the minimum update value of the previous frame.

[0025] The updated frame data of the current frame is obtained by performing a frame cyclic comparison based on the initial frame data of the current frame and the updated frame data of the previous frame; the updated frame data of the current frame includes the current frame update average value, the current frame update maximum value, and the current frame update minimum value.

[0026] The intermediate data is obtained based on at least one frame cyclic comparison. The obtained current frame update average is used as the frame cumulative average, the current frame update maximum value is used as the frame comparison maximum value, and the current frame update minimum value is used as the frame comparison minimum value. When the previous frame is the first frame, the first frame update average is the first frame initial average, the first frame update maximum value is the first frame initial maximum value, and the first frame update minimum value is the first frame initial minimum value.

[0027] Preferably, obtaining the updated frame data of the current frame by performing a frame cyclic comparison based on the initial frame data of the current frame and the updated frame data of the previous frame includes:

[0028] The current frame update average is obtained by averaging the initial average of the current frame and the update average of the previous frame.

[0029] The maximum update value of the previous frame is compared with the initial maximum value of the current frame to obtain a first comparison result, and the maximum update value of the current frame is updated according to the first comparison result;

[0030] The minimum value updated in the previous frame is compared with the initial minimum value in the current frame to obtain a second comparison result, and the minimum value updated in the current frame is updated based on the second comparison result.

[0031] Preferably, the process further includes the following steps before obtaining the intermediate data:

[0032] Compare the number of frame loop comparisons with a threshold number;

[0033] If the number of frame comparisons is greater than or equal to the threshold number, then the intermediate data is obtained based on the current frame update data;

[0034] If the number of frame comparisons is less than the threshold number, the frame comparison continues.

[0035] Preferably, if it is determined that the number of cyclic comparisons is less than the number threshold, and / or the intermediate data does not meet the set conditions, the detection method further includes: comparing the current frame number with the target frame number; if the current frame number is less than the target frame number, then continue the frame cyclic comparison; if the current frame number is greater than or equal to the target frame number, then the intermediate data is used as the calculation data for the indicator data.

[0036] Preferably, the detection method further includes the step of storing the current frame cyclic update data obtained after each frame cyclic comparison.

[0037] To achieve the above and other related objectives, the present invention also provides a detection device for CIS dark current correction quality, which is applicable to the above-mentioned detection method for CIS dark current correction quality. The detection device includes a data acquisition module, an adder, a comparator module, a memory, and a second comparison module.

[0038] The data acquisition module is configured to acquire sampled data of the pixel array in each frame;

[0039] The adder is coupled to the data acquisition module and is configured to process the sampled data of each frame to obtain an initial average value, and to obtain the cumulative average value of the frames based on the initial average value.

[0040] The first comparator module is coupled to the data acquisition module and is configured to process the sampled data of each frame to obtain the initial maximum value and the initial minimum value, and to obtain the frame comparison maximum value and the frame comparison minimum value based on the initial maximum value and the initial minimum value;

[0041] The memory is coupled to the adder and the first comparator module respectively, and is configured to store the intermediate data obtained by the adder and the first comparator module.

[0042] The second comparator module is coupled to the memory and configured to compare the intermediate data and set conditions to obtain the index data.

[0043] Preferably, the first comparison module includes a first comparator and a second comparator coupled to the data acquisition module, when performing the frame cyclic comparison:

[0044] The data acquisition module is configured to acquire the current frame sampling data of the pixel array;

[0045] The adder is configured to process the sampled data of the current frame to obtain the initial average value of the current frame, and to process the initial average value of the current frame and the updated average value of the previous frame to obtain the updated average value of the current frame.

[0046] The first comparator is configured to process the current frame sampled data to obtain the current frame initial maximum value, and compare the current frame initial maximum value with the previous frame updated maximum value to obtain the current frame updated maximum value;

[0047] The second comparator is configured to process the current frame sampled data to obtain the initial minimum value of the current frame, and compare the initial minimum value of the current frame with the updated minimum value of the previous frame to obtain the updated minimum value of the current frame;

[0048] The memory is further configured to store the current frame update average value, the current frame update maximum value, and the current frame update minimum value to obtain the intermediate data, and the memory is further configured to store data corresponding to the set conditions for obtaining the indicator data;

[0049] The second comparison module includes a third comparator, which is coupled to the memory to obtain the intermediate data in the memory and the data corresponding to the set conditions to obtain the index data.

[0050] To achieve the above and other related objectives, the present invention provides an electronic device comprising a processor and a memory, wherein the memory stores a computer program executable on the processor, and the computer program, when executed by the processor, implements the steps of the above-described method for detecting the dark current correction quality of CIS.

[0051] To achieve the above and other related objectives, the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, performs the steps of the above-described method for detecting the dark current correction quality of CIS.

[0052] As described above, the method, apparatus, computer storage medium, and electronic device for detecting the dark current correction quality of CIS of the present invention have the following beneficial effects:

[0053] The method and apparatus for detecting CIS dark current correction quality proposed in this invention effectively detects CIS dark current correction quality in an automated manner, obtaining CIS dark current correction image quality with minimal hardware circuit cost and high computational accuracy, thereby improving product quality classification efficiency. Attached Figure Description

[0054] Figure 1 The diagram shows a flowchart of the method for detecting the dark current correction quality of CIS according to the present invention.

[0055] Figure 2 The diagram shows a flowchart of a method for detecting the dark current correction quality of CIS in an embodiment of the present invention.

[0056] Figure 3 This diagram illustrates the flow chart of a method for detecting the dark current correction quality of CIS in another embodiment of the present invention.

[0057] Figure 4 The diagram shows the structure of the detection device for CIS dark current correction quality of the present invention. Detailed Implementation

[0058] The following specific examples illustrate the implementation of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention.

[0059] Please see Figures 1-4 It should be noted that the illustrations provided in this embodiment are only schematic representations of the basic concept of the present invention. Therefore, the drawings only show the components related to the present invention and are not drawn according to the actual number, shape and size of the components in the actual implementation. In the actual implementation, the form, quantity and proportion of each component can be arbitrarily changed, and the layout of the components may also be more complex.

[0060] Dark current refers to the reverse DC current generated when there is no incident light under the condition that the PN junction is reverse biased. Therefore, the process of detecting the dark current correction quality of CIS in this invention needs to be carried out under darkness.

[0061] Method Implementation Examples:

[0062] like Figure 1 The diagram shows a flowchart of a method for detecting the dark current correction quality of a CIS according to the present invention. Figure 1The method for detecting the dark current correction quality of CIS according to the present invention is described in detail. The detection method is performed under dark conditions and includes at least the following steps:

[0063] S1, acquire the sampled data of the pixel array in each frame;

[0064] Specifically, in one example, the sampled data of the pixel array can be the pixel value corresponding to each pixel, for example, it can be the data read through the bitline and quantized by the existing readout circuit; in another example, when the pixel array samples the data of each frame, it samples according to the color channel. For example, in one embodiment, the color channel includes the R channel, Gr channel, Gb channel and B channel, resulting in four-channel sampled data.

[0065] In this embodiment of the invention, the sampled data is the value of the entire pixel array for subsequent processing. As another implementation, the pixel array can be divided into several blocks by region before sampling to obtain data with partial pixel values ​​for subsequent processing. In this way, when processing the sampled data in subsequent steps, pixels in a partial region can be directly selected for statistics, thereby saving energy. It should be noted that the selected regions should be dispersed to represent the entire pixel array as much as possible to ensure the accuracy of the detection results. For example, the sampling data center corresponding to the pixel array and five equally sized blocks formed by the four corners can be selected for processing.

[0066] S2, process the sampled data of each frame to obtain the initial frame data of the corresponding frame; the initial frame data includes the initial average value, the initial maximum value and the initial minimum value;

[0067] In one embodiment, the sampled data is divided into several blocks, and at least one block is selected for processing to obtain the initial frame data corresponding to the frame. The following description uses the entire sampled data corresponding to the selected pixel array.

[0068] The processing described in this invention includes, but is not limited to, summation and comparison; when averaging the sampled data of a frame, the initial average value corresponding to that frame is obtained; when comparing the sampled data of a frame, the initial maximum value and initial minimum value in the sampled data of that frame are obtained. Therefore, the initial frame data includes the initial average value, the initial maximum value, and the initial minimum value.

[0069] In this embodiment of the invention, the sampled data of each frame can be processed according to the color channels, as follows:

[0070] The sampled data from the R channel are summed to obtain M1, the sampled data from the Gr channel are summed to obtain M2, the sampled data from the Gb channel are summed to obtain M3, and the sampled data from the B channel are summed to obtain M4. Alternatively, when processing without channel segmentation, the summation of the sampled data is equivalent to summing the sampled data from all channels, resulting in the cumulative value of the sampled data for that frame: M = M1 + M2 + M3 + M4. Similarly, the cumulative value for the next frame is N = N1 + N2 + N3 + N4, and so on. Finally, the summation values ​​of the sampled data for each frame are averaged to obtain the initial average value corresponding to that frame's sampled data. Specifically, when processing without channel segmentation, one initial average value is obtained for each frame; when processing by channel segmentation, such as with four channels, four initial average values ​​are obtained for each frame.

[0071] When comparing sampled data, you can directly compare all sampled data of the R channel, Gr channel, Gb channel and B channel (without channel-specific processing) to obtain the initial maximum value Mmax and initial minimum value Mmin of the current frame of the pixel array; or you can compare the maximum and minimum values ​​of each channel first to obtain the four sets of initial maximum values ​​and initial minimum values.

[0072] S3, process the initial frame data to obtain intermediate data; the intermediate data includes the cumulative average value of frames, the maximum value after frame comparison, and the minimum value after frame comparison;

[0073] In this embodiment of the invention, the intermediate data is obtained using a frame cyclic comparison method. In one embodiment, such as... Figure 2 As shown, it includes the following steps:

[0074] S31, obtain the initial frame data of the current frame, including the initial average value, the initial maximum value, and the initial minimum value of the current frame; it should be noted that the initial average value of the current frame can be understood and obtained in accordance with the initial average value of each frame as described above in this invention. For example, the initial average value of the current frame is the initial average value of the initial frame data obtained from the sampling data corresponding to the pixel array of the current frame, which is obtained by summing and averaging based on the pixel values ​​of the current frame; and so on, to obtain the initial maximum value and the initial minimum value of the current frame in this step.

[0075] S32, obtain the update frame data of the previous frame, the update frame data includes the average update value, the maximum update value, and the minimum update value of the previous frame; wherein, the update data of the previous frame may have been stored in the memory, and the data of the previous frame is obtained from the memory in this step.

[0076] S33, perform frame loop comparison based on the initial frame data of the current frame and the updated frame data of the previous frame to obtain the updated frame data of the current frame; wherein, the updated frame data of the current frame includes the average update value, the maximum update value, and the minimum update value of the current frame.

[0077] In a preferred embodiment of the present invention, the current frame update data obtained after each frame cyclic comparison is stored. Specifically, after processing and obtaining the frame comparison data of the current frame, the frame comparison data is first stored in a memory (such as a static random access memory). An idle storage module on the chip can be used to avoid additional hardware overhead.

[0078] Specifically, the average of the initial average value of the current frame and the average update value of the previous frame are averaged to obtain the average update value of the current frame; the maximum update value of the previous frame and the maximum update value of the current frame are compared to obtain a first comparison result, and the maximum update value of the current frame is obtained based on the first comparison result, i.e., the larger one is taken as the maximum update value of the current frame; the minimum update value of the previous frame and the minimum update value of the current frame are compared to obtain a second comparison result, and the minimum update value of the current frame is obtained based on the second comparison result, i.e., the smaller one is taken as the minimum update value of the current frame. Additionally, after obtaining the update data of the current frame, the process may further include a step of storing the updated value in memory for subsequent cyclic comparisons.

[0079] S34, based on at least one frame cyclic comparison to obtain the intermediate data, the current frame update average is used as the frame cumulative average, the current frame update maximum is used as the frame comparison maximum, and the current frame update minimum is used as the frame comparison minimum; when the previous frame is the first frame, the update average of the first frame is the initial average of the first frame, the update maximum of the first frame is the initial maximum of the first frame, and the update minimum of the first frame is the initial minimum of the first frame. Specifically, the indicator data is obtained by comparing the frame cumulative average, the frame comparison maximum, and the frame comparison minimum with data based on set conditions.

[0080] More specifically, if the average value of the first frame's sampled data is directly stored as the updated average value of the first frame; after obtaining the average value of the second frame's sampled data, the average of the average value of the first frame's sampled data and the average of the second frame's sampled data is used as the updated average value of the second frame; further, the frame loop comparison continues, and the average of the third frame's average value and the updated average value of the second frame is used as the updated average value of the third frame, and so on, calculating the updated average value of subsequent frames. In one implementation, the updated frame data of the Nth frame is used as intermediate data, where N≥2; for example, N is 2, and to save efficiency, the intermediate data is determined after one frame loop comparison, then the frame average value of the intermediate data is the updated average value of the second frame. If the intermediate data is compared with the set conditions, and the conditions are met, the index data is obtained; otherwise, the frame loop comparison continues. This can be understood as each frame loop comparison obtaining intermediate data and comparing it with the set conditions to see if the index data is obtained.

[0081] More specifically, if the initial maximum value in the initial frame data of the current frame is greater than the updated maximum value after frame comparison of the previous frame stored in memory, then the initial maximum value in the initial frame data of the current frame is updated to the updated maximum value after frame comparison of the current frame. If the initial maximum value in the initial frame data of the current frame is less than the updated maximum value after frame comparison of the previous frame stored in memory, then the updated maximum value after frame comparison in the current memory remains unchanged and is used as the updated maximum value of the current frame. If the initial minimum value in the initial frame data of the current frame is less than the updated minimum value after frame comparison of the previous frame stored in memory, then the initial minimum value in the initial frame data of the current frame is updated to the updated minimum value after frame comparison of the current frame. If the initial minimum value of the current frame is greater than the updated minimum value after frame comparison of the previous frame stored in memory, then the updated minimum value after frame comparison in the current memory remains unchanged and is used as the updated minimum value of the current frame, so as to obtain intermediate data for comparison.

[0082] S4, the intermediate data is processed to obtain index data, and the intermediate data is compared with the set conditions to obtain index data; the index data includes a corrected mean value obtained based on the cumulative average value of the frames and a critical difference value obtained based on the maximum value and the minimum value after the frame comparison.

[0083] In this embodiment of the invention, the intermediate data when a set condition is met is used as the calculation data to obtain the index data; the set condition is: the cumulative average value of the frames is greater than a second set threshold, and / or, the difference between the maximum value and the minimum value after frame comparison is greater than a third set threshold. In one embodiment, if the condition is not met, frame cyclic comparison continues. The second and third set thresholds can be set according to actual needs, such as power consumption, dark current correction quality requirements, time overhead, chip stability, etc.

[0084] In other words, the intermediate data corresponding to the conditions being met is used as the calculation data. The average value of the frames accumulated in the intermediate data is used as the correction mean. The difference between the maximum and minimum values ​​after frame comparison is used to obtain the critical difference. In one example, the 10th frame can be used as the current frame, the update average value of the 10th frame can be used as the correction mean, and the difference between the update maximum and update minimum values ​​of the 10th frame can be used to obtain the critical difference.

[0085] To improve detection accuracy, as a preferred embodiment, before obtaining intermediate data, the method may include comparing the number of frame loop comparisons with a threshold number; see [link to previous document]. Figure 3 As shown, if the number of frame comparisons is greater than or equal to the threshold number, the updated data of the current frame is used as the intermediate data to obtain the index data; if the number of frame comparisons is less than the threshold number, the frame comparison continues. The threshold number can be set according to actual needs, such as power consumption, dark current correction quality requirements, time overhead, chip stability, etc., and can be 5 times, 10 times, etc. Assuming the number of comparisons is set to T, the intermediate data is processed continuously for each frame according to step S2. When updating to the Tth frame, the intermediate data of the Tth frame is processed to obtain the index data of the pixel array.

[0086] See further examples. Figure 3 As shown, if it is determined that the number of loop comparisons is less than the threshold number, and / or the intermediate data does not exceed the set condition, or the intermediate data does not meet the set condition, the detection method further includes the steps of: comparing the current frame number with the target frame number; if the current frame number is less than the target frame number, then continuing the frame loop comparison; if the current frame number is greater than or equal to the target frame number, then obtaining the intermediate data based on the current frame update data as the calculation data for the indicator data. The target frame number can be set according to actual needs, such as based on power consumption and dark current correction quality requirements, and can be 20 frames, 50 frames, etc.

[0087] In one example, when the sampling data of each channel is obtained, the initial average value, initial maximum value, and initial minimum value of each channel, such as channel R, are compared in the manner described above in this embodiment to obtain the index data corresponding to that channel. That is, the above-described processing of the sampling data of the entire pixel array is only processed for a certain channel pixel in the pixel array to obtain the dark current correction detection result. For example, for a four-channel pixel array, four sets of correction detection results can be obtained, which can then be further classified.

[0088] In a further example, the process of obtaining the indicator data also includes: comparing the difference between the initial average values ​​corresponding to any two color channels with a first preset threshold, and obtaining the indicator data when the difference between the initial average values ​​corresponding to the color channels is less than the first preset threshold. The first preset threshold can be set according to actual needs. That is, the intermediate data used as calculation data to obtain the indicator data must, in addition to satisfying the preset conditions (satisfying the second preset threshold and / or satisfying the third preset threshold), also satisfy the condition of the first preset threshold.

[0089] S5, make a judgment based on the index data, and realize the detection of CIS dark current correction quality based on the judgment result.

[0090] In this embodiment of the invention, the quality of the OB value of dark current correction is determined based on the correction mean in the index data; the stability quality of dark current correction is determined based on the critical difference in the index data, wherein the critical difference is the difference between the maximum value and the minimum value after frame comparison.

[0091] In this invention, the quality of dark current correction is detected and judged based on the aforementioned index data. This is achieved by measuring the OB value of the pixel array of the CIS after dark current correction through the cumulative average value of multiple frames. The OB value can be any index known in the prior art that characterizes the level of dark current correction. If the obtained cumulative average value of the frames fluctuates little around a set OB threshold, it indicates that the OB value of dark current correction is good. If it exceeds the set OB threshold, it indicates that it is poor. This can be defined according to actual needs.

[0092] Specifically, in one example, the set OB threshold can be a range value, for example, represented by a first set constant and a second set constant. The frame cumulative average value is compared with the set OB threshold. Exceeding the set OB threshold indicates that the frame cumulative average value is less than the first set constant or the frame cumulative average value is greater than the second set constant. That is, in this example, when the frame cumulative average value is less than the first set constant, it is determined to be a poor OB value for dark current correction; when the first set constant is less than the frame cumulative average value and less than the second set constant, it is determined to be a good OB value for dark current correction; when the frame cumulative average value is greater than the second set constant, it is determined to be a poor OB value for dark current correction.

[0093] The PEAK-PEAK value, calculated from the maximum and minimum values ​​after frame comparison, measures the stability of CIS dark current correction. The smaller the difference between the maximum and minimum values ​​after frame comparison (i.e., the critical difference), the better the stability of dark current correction.

[0094] In one example, the CIS dark current correction level information can be automatically output based on the judgment result, and the OTP programming program can be started to program this information; the CIS dark current correction quality can be detected through the CIS dark current correction level information.

[0095] To more accurately measure the quality of dark current correction, the data after power-on stabilization can be processed. Since the data in the first few frames after power-on is unstable, the statistics of the sampling data in the first few frames are skipped during processing. The specific number of frames to skip can be set based on experience such as power-on stability; that is, a threshold number is set to obtain the index data based on intermediate data. Furthermore, to improve detection efficiency, the number of updates can be disregarded when the average cumulative value, the maximum value of the pixel array, and the minimum value of the pixel array exceed a set value (perhaps the result is obtained after only one frame loop).

[0096] By detecting the dark current correction quality of CIS in this invention, the dark current quality of the chip can be accurately classified.

[0097] Device Example:

[0098] To achieve the above-mentioned technical objectives, the present invention also provides a detection device for CIS dark current correction quality, such as... Figure 4 As shown, a detection method applicable to the CIS dark current correction quality described in any of the above schemes is provided. The detection device includes a data acquisition module, an adder, a first comparator module, a memory, and a second comparator module, wherein:

[0099] The data acquisition module is configured to acquire the sampled data of the pixel array in each frame;

[0100] The adder is coupled to the data acquisition module and is configured to process the sampled data of each frame to obtain the initial average value, and to obtain the cumulative average value of the frames based on the initial average value.

[0101] The first comparator module is coupled to the data acquisition module and is configured to process the sampled data of each frame to obtain the initial maximum value and the initial minimum value, and to obtain the frame comparison maximum value and the frame comparison minimum value based on the initial maximum value and the initial minimum value;

[0102] The memory is coupled to the adder and the first comparator module respectively, and is configured to store the intermediate data acquired by the adder and the first comparator module.

[0103] The second comparison module is coupled to the memory and configured to compare the intermediate data and set conditions to obtain the index data.

[0104] As an example, see further. Figure 4 As shown, the first comparison module includes a first comparator and a second comparator coupled to the data acquisition module. When performing the frame cyclic comparison:

[0105] The data acquisition module is configured to acquire the current frame sampling data of the pixel array;

[0106] The adder is configured to process the sampled data of the current frame to obtain the initial average value of the current frame, and to process the initial average value of the current frame and the updated average value of the previous frame to obtain the updated average value of the current frame.

[0107] The first comparator is configured to process the current frame sampled data to obtain the current frame initial maximum value, and compare the current frame initial maximum value with the previous frame updated maximum value to obtain the current frame updated maximum value;

[0108] The second comparator is configured to process the current frame sampled data to obtain the initial minimum value of the current frame, and compare the initial minimum value of the current frame with the updated minimum value of the previous frame to obtain the updated minimum value of the current frame;

[0109] The memory is further configured to store the current frame update average value, the current frame update maximum value, and the current frame update minimum value to obtain the intermediate data, and the memory is further configured to store data corresponding to the set conditions for obtaining the indicator data;

[0110] The second comparison module includes a third comparator, which is coupled to the memory to obtain the intermediate data in the memory and the data corresponding to the set conditions to obtain the index data.

[0111] In this embodiment of the invention, the memory of the detection device is in static random access memory, which can utilize an idle on-chip storage module, avoiding additional hardware overhead. Furthermore, the usage of the detection device in this embodiment can be found in the description of the detection method embodiments of the present invention; the detection method can be implemented based on this detection device, and will not be repeated here.

[0112] Examples of computer-readable storage media:

[0113] To achieve the above-mentioned technical objectives, the present invention also proposes a computer-readable storage medium storing a data processing program; when the data processing program is executed by at least one processor, the at least one processor performs the steps of the above-described method for detecting the CIS dark current correction quality. The method for detecting the CIS dark current correction quality has been described in detail in the method embodiments and will not be repeated here.

[0114] Electronic device example:

[0115] The present invention also proposes an electronic device, including a processor, a memory, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the computer program, implements the steps of the above-described method for detecting the dark current correction quality of CIS.

[0116] The processor can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc., or it can be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), an off-the-shelf programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this application. The general-purpose processor can be a microprocessor or any conventional processor.

[0117] The electronic devices of this invention exist in various forms, including but not limited to:

[0118] (1) Mobile communication devices: These devices are characterized by their mobile communication capabilities and primarily aim to provide voice and data communication. These terminals include: smartphones (e.g., iPhones), multimedia phones, feature phones, and low-end phones, etc.

[0119] (2) Ultra-mobile personal computer devices: These devices fall under the category of personal computers, possessing computing and processing capabilities, and generally also have mobile internet access features. These terminals include PDAs, MIDs, and UMPCs, such as the iPad.

[0120] (3) Portable entertainment devices: These devices can display and play multimedia content. This category includes audio and video players (e.g., iPods), handheld game consoles, e-book readers, as well as smart toys and portable car navigation devices.

[0121] (4) Server: A device that provides computing services. The components of a server include a processor, hard disk, memory, system bus, etc. Servers are similar to general computer architectures, but because they need to provide highly reliable services, they have higher requirements in terms of processing power, stability, reliability, security, scalability, and manageability.

[0122] (5) Other electronic devices with data interaction functions.

[0123] It should be noted that, depending on the implementation needs, the various components / steps described in the embodiments of this application can be broken down into more components / steps, or two or more components / steps or parts of the operation of components / steps can be combined into new components / steps to achieve the purpose of the embodiments of this application.

[0124] In summary, this invention achieves high-quality CIS dark current correction images with minimal hardware circuitry cost and high computational accuracy, thereby improving product quality classification efficiency and enabling real-time automation. Therefore, this invention effectively overcomes the various shortcomings of existing technologies and possesses high industrial applicability.

[0125] The above embodiments are merely illustrative of the principles and effects of the present invention and are not intended to limit the invention. Any person skilled in the art can modify or alter the above embodiments without departing from the spirit and scope of the present invention. Therefore, all equivalent modifications or alterations made by those skilled in the art without departing from the spirit and technical concept disclosed in the present invention should still be covered by the claims of the present invention.

Claims

1. A method for detecting the dark current correction quality of a CIS (Content Injection System), performed under dark conditions, characterized in that, The detection method includes at least the following steps: Obtain the sampled data of the pixel array in each frame; The sampled data of each frame is processed to obtain the initial frame data of the corresponding frame; the initial frame data includes the initial average value, the initial maximum value, and the initial minimum value; The initial frame data is processed to obtain intermediate data; the intermediate data includes the cumulative average value of frames, the maximum value after frame comparison, and the minimum value after frame comparison. The indicator data is obtained based on the intermediate data; the indicator data includes the corrected mean value obtained based on the cumulative average value of the frames and the critical difference value obtained based on the maximum value and the minimum value after frame comparison; the intermediate data that meets the set conditions is used as the calculation data to obtain the indicator data; the set conditions are: the cumulative average value of the frames is greater than a second set threshold, and / or, the difference between the maximum value and the minimum value after frame comparison is greater than a third set threshold; The judgment is made based on the aforementioned indicator data, and the quality of CIS dark current correction is detected based on the judgment result. The intermediate data is obtained by using a frame cyclic comparison method, which includes the following steps: Obtain the initial frame data of the current frame, which includes the initial average value, the initial maximum value, and the initial minimum value of the current frame. Obtain the update frame data of the previous frame, wherein the update frame data of the previous frame includes the average update value, the maximum update value, and the minimum update value of the previous frame. The updated frame data of the current frame is obtained by performing a frame cyclic comparison based on the initial frame data of the current frame and the updated frame data of the previous frame. The updated frame data of the current frame includes the average update value, the maximum update value, and the minimum update value of the current frame. The intermediate data is obtained based on at least one frame cyclic comparison. The obtained current frame update average is used as the frame cumulative average, the current frame update maximum value is used as the frame comparison maximum value, and the current frame update minimum value is used as the frame comparison minimum value. When the previous frame is the first frame, the first frame update average is the first frame initial average, the first frame update maximum value is the first frame initial maximum value, and the first frame update minimum value is the first frame initial minimum value.

2. The method for detecting the dark current correction quality of CIS according to claim 1, characterized in that, The method of obtaining the initial frame data includes: dividing the sampled data into several blocks, selecting at least one of the blocks for processing to obtain the initial frame data of the corresponding frame.

3. The method for detecting the dark current correction quality of CIS according to claim 1, characterized in that, The sampled data of a frame are averaged to obtain the initial average value corresponding to that frame; and / or, the sampled data of a frame are compared to obtain the initial maximum value and the initial minimum value corresponding to that frame.

4. The method for detecting the dark current correction quality of CIS according to claim 1, characterized in that, The sampled data for each frame is processed according to the color channels to obtain the corresponding initial frame data.

5. The method for detecting the dark current correction quality of CIS according to claim 4, characterized in that, The process of obtaining the index data also includes: comparing the difference between the initial average values ​​corresponding to any two color channels with a first set threshold, and obtaining the index data when the difference between the initial average values ​​corresponding to the color channels is less than the first set threshold.

6. The method for detecting the dark current correction quality of CIS according to claim 1, characterized in that, The OB quality of dark current correction is determined based on the correction mean in the index data; and / or the stability quality of dark current correction is determined based on the critical difference in the index data, wherein the critical difference is the difference between the maximum value and the minimum value after the frame comparison.

7. The method for detecting the dark current correction quality of CIS according to claim 1, characterized in that, The updated frame data of the current frame is obtained by performing a frame loop comparison based on the initial frame data of the current frame and the updated frame data of the previous frame, including: The current frame update average is obtained by averaging the initial average of the current frame and the update average of the previous frame. The maximum update value of the previous frame is compared with the initial maximum value of the current frame to obtain a first comparison result, and the maximum update value of the current frame is updated according to the first comparison result; The minimum value updated in the previous frame is compared with the initial minimum value in the current frame to obtain a second comparison result, and the minimum value updated in the current frame is updated based on the second comparison result.

8. The method for detecting the dark current correction quality of CIS according to claim 1, characterized in that, The process before obtaining the intermediate data also includes the following steps: Compare the number of frame loop comparisons with a threshold number; If the number of frame comparisons is greater than or equal to the threshold number, then the intermediate data is obtained based on the current frame update data; If the number of frame comparisons is less than the threshold number, the frame comparison continues.

9. The method for detecting the dark current correction quality of CIS according to claim 8, characterized in that, If it is determined that the number of cyclic comparisons is less than the number threshold, and / or the intermediate data does not meet the set conditions, the detection method includes the steps of: comparing the current frame number with the target frame number; if the current frame number is less than the target frame number, then continuing the frame cyclic comparison; if the current frame number is greater than or equal to the target frame number, then the intermediate data is used as the calculation data for the indicator data.

10. The method for detecting the dark current correction quality of CIS according to claim 1, characterized in that, The detection method further includes the step of storing the current frame cyclic update data obtained after each frame cyclic comparison.

11. A device for detecting the dark current correction quality of a CIS (Computer Integrated System), applicable to the method for detecting the dark current correction quality of a CIS as described in any one of claims 1-10, characterized in that, The detection device includes a data acquisition module, an adder, a first comparator module, a memory, and a second comparator module, wherein: The data acquisition module is configured to acquire the sampled data of the pixel array in each frame; The adder is coupled to the data acquisition module and is configured to process the sampled data of each frame to obtain the initial average value, and to obtain the cumulative average value of the frames based on the initial average value. The first comparator module is coupled to the data acquisition module and is configured to process the sampled data of each frame to obtain the initial maximum value and the initial minimum value, and to obtain the frame comparison maximum value and the frame comparison minimum value based on the initial maximum value and the initial minimum value; The memory is coupled to the adder and the first comparator module respectively, and is configured to store the intermediate data acquired by the adder and the first comparator module. The second comparator module is coupled to the memory and configured to compare the intermediate data and set conditions to obtain the index data.

12. The detection device for CIS dark current correction quality according to claim 11, characterized in that, The first comparator module includes a first comparator and a second comparator coupled to the data acquisition module. When performing the frame cyclic comparison: The data acquisition module is configured to acquire the current frame sampling data of the pixel array; The adder is configured to process the sampled data of the current frame to obtain the initial average value of the current frame, and to process the initial average value of the current frame and the updated average value of the previous frame to obtain the updated average value of the current frame. The first comparator is configured to process the current frame sampled data to obtain the current frame initial maximum value, and compare the current frame initial maximum value with the previous frame updated maximum value to obtain the current frame updated maximum value; The second comparator is configured to process the current frame sampled data to obtain the initial minimum value of the current frame, and compare the initial minimum value of the current frame with the updated minimum value of the previous frame to obtain the updated minimum value of the current frame; The memory is further configured to store the current frame update average value, the current frame update maximum value, and the current frame update minimum value to obtain the intermediate data, and the memory is further configured to store data corresponding to the set conditions for obtaining the indicator data; The second comparator module includes a third comparator, which is coupled to the memory to obtain the intermediate data in the memory and the data corresponding to the set conditions to obtain the index data.

13. An electronic device, characterized in that, The electronic device includes a processor and a memory, the memory storing a computer program that can run on the processor, the computer program being executed by the processor to implement the steps of the method for detecting the dark current correction quality of CIS as described in any one of claims 1-10.

14. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it performs the steps of the method for detecting the dark current correction quality of CIS as described in any one of claims 1-10.

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