Correction method, correction device, image sensor, and computer program product
By determining the capacitance influence factor and correction formula in the image sensor, and performing correction calculations on the pixel array, the quantization interference problem between adjacent color channels is solved, thus improving image quality.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- SMARTSENS TECH (SHANGHAI) CO LTD
- Filing Date
- 2024-12-20
- Publication Date
- 2026-06-23
AI Technical Summary
As pixel size gradually shrinks, the electrical interactions and coupling between adjacent color channels become increasingly severe, leading to increased quantization errors and affecting image quality.
By determining the capacitance influence factor and preset correction formula in the pixel array, the original quantization value is corrected based on the equivalent circuit, thereby reducing quantization interference between adjacent color channels.
It improves the output image quality of the image sensor and reduces quantization interference between adjacent color channels.
Smart Images
Figure CN122269162A_ABST
Abstract
Description
Technical Field
[0001] This application belongs to the field of image sensor technology, and particularly relates to a calibration method, calibration device, image sensor and computer program product. Background Technology
[0002] An image sensor's pixel array is specifically composed of pixel units of different photosensitive colors arranged together. For the same light signal, the quantization values of different color channels differ because different pixel units have different photosensitive intensities. As pixel sizes gradually shrink, especially at the sub-micron level, the pixel units in the pixel array become closer together. This leads to increasingly severe electrical interactions and coupling between adjacent color channels, further increasing quantization errors and thus affecting the output image quality. Summary of the Invention
[0003] This application provides a correction method, correction device, image sensor, and computer program product that can reduce quantization interference between adjacent color channels, thereby helping to improve the quality of the output image.
[0004] Firstly, this application provides a correction method, including:
[0005] Determine the first raw quantization value of the first pixel and the second raw quantization value of the second pixel, wherein the first pixel is any pixel in the pixel array, and the second pixel is a pixel that is in the same row as the first pixel in the pixel array, is adjacent to the first pixel, and has a different color from the first pixel;
[0006] Obtain the capacitance influence factor of the pixel array. The capacitance influence factor is used to express the influence of parasitic capacitance in the pixel array.
[0007] The first original quantization value is corrected and calculated based on the first original quantization value, the second original quantization value, the capacitance influence factor, and the preset correction formula to obtain the first corrected quantization value. The first corrected quantization value is the quantization value of the first pixel after correction. The correction formula is derived through the equivalent circuit of the pixel array.
[0008] Secondly, this application provides a calibration device, comprising:
[0009] The first determining module is used to determine the first original quantization value of the first pixel and the second original quantization value of the second pixel, wherein the first pixel is any pixel in the pixel array, and the second pixel is a pixel that is in the same row as the first pixel in the pixel array, adjacent to the first pixel, and has a different color from the first pixel.
[0010] The acquisition module is used to acquire the capacitance influence factor of the pixel array. The capacitance influence factor is used to express the influence of parasitic capacitance in the pixel array.
[0011] The calculation module is used to perform correction calculation on the first original quantization value based on the first original quantization value, the second original quantization value, the capacitance influence factor and the preset correction formula to obtain the first corrected quantization value. The first corrected quantization value is the quantization value after correction of the first pixel. The correction formula is derived through the equivalent circuit of the pixel array.
[0012] Thirdly, this application provides an image sensor, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps of the method described in the first aspect.
[0013] Fourthly, this application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the method described in the first aspect above.
[0014] Fifthly, this application provides a computer program product comprising a computer program that, when executed by one or more processors, implements the steps of the method described in the first aspect.
[0015] The advantages of this application compared to existing technologies are as follows: This application's solution considers the impact of parasitic capacitance in the pixel array and the quantization values of adjacent pixels of different colors on quantization, and derives a correction formula in advance through the equivalent circuit of the pixel array. In this way, after reading the original quantization values of the pixel array, the image sensor can perform correction by iterating through the original quantization values of each pixel based on this correction formula. Therefore, the image sensor can reduce quantization interference between adjacent color channels, thereby helping to improve the output image quality.
[0016] It is understood that the beneficial effects of the second to fifth aspects mentioned above can be found in the relevant descriptions in the first aspect mentioned above, and will not be repeated here. Attached Figure Description
[0017] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0018] Figure 1 This is a schematic diagram of the pixel array structure provided in an embodiment of this application;
[0019] Figure 2This is a schematic diagram illustrating the implementation process of the correction method provided in the embodiments of this application;
[0020] Figure 3 This is a schematic diagram of the capacitive coupling model between the lcg node and the FD node provided in the embodiments of this application;
[0021] Figure 4 This is a schematic diagram of the structure of the correction device provided in the embodiments of this application;
[0022] Figure 5 This is a schematic diagram of the structure of the image sensor provided in the embodiments of this application. Detailed Implementation
[0023] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.
[0024] It should be understood that, when used in this application specification and the appended claims, the term "comprising" indicates the presence of the described features, integrals, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or a collection thereof.
[0025] It should also be understood that the term “and / or” as used in this application specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.
[0026] As used in this application specification and the appended claims, the term "if" may be interpreted, depending on the context, as "when," "once," "in response to determination," or "in response to detection." Similarly, the phrase "if determined" or "if detected [the described condition or event]" may be interpreted, depending on the context, as meaning "once determined," "in response to determination," "once detected [the described condition or event]," or "in response to detection [the described condition or event]."
[0027] Furthermore, in the description of this application and the appended claims, the terms "first" and "second," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.
[0028] References to "one embodiment" or "some embodiments" in this specification mean that one or more embodiments of this application include a specific feature, structure, or characteristic described in connection with that embodiment. Therefore, the phrases "in one embodiment," "in some embodiments," "in other embodiments," "in still other embodiments," etc., appearing in different parts of this specification do not necessarily refer to the same embodiment, but rather mean "one or more, but not all, embodiments," unless otherwise specifically emphasized. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless otherwise specifically emphasized.
[0029] An image sensor's pixel array is specifically composed of pixel units that are sensitive to different colors of light. Please refer to [link / reference]. Figure 1 , Figure 1 A schematic diagram of a pixel array structure is given. Figure 1 In the illustration, pixel units are divided into four categories: R, Gr, Gb, and B. Pixel unit R is used to quantize red light, pixel units Gr and Gb are used to quantize green light, and pixel unit B is used to quantize blue light. The quantization results are then superimposed to obtain the final imaging data. Under the same light intensity, the number of electrons produced by the photoelectric effect of red, green, and blue light differs, resulting in different voltages at the floating diffusion (FD) nodes. Ideally, these voltages are quantized individually, but in practice, they are coupled together by parasites in the pixel array, causing voltage distortion at the FD nodes and affecting the final quantization output.
[0030] Furthermore, as pixel size gradually shrinks, especially after entering the submicron level, the individual pixel units in the pixel array become closer together. This leads to increasingly severe electrical interactions and coupling between adjacent color channels, further increasing quantization errors.
[0031] Based on this, embodiments of this application propose a correction method, correction device, image sensor, and computer program product that can reduce quantization interference between adjacent color channels, thereby helping to improve the output image quality. Specific embodiments are described below.
[0032] This application provides a correction method that can be applied to an image processor; that is, the image processor is the entity executing the correction method. Please refer to... Figure 2 The correction method provided in this application includes:
[0033] Step 201: Determine the first raw quantization value of the first pixel and the second raw quantization value of the second pixel.
[0034] The image sensor can first read out the raw quantized values of each pixel in the pixel array. This raw quantized value is understood to be the uncorrected quantized value obtained through the pixel readout circuit. In this embodiment, the raw quantized value of each pixel needs to be corrected, thus the concepts of a first pixel and a second pixel are proposed. The first pixel refers to any pixel in the pixel array, and the second pixel refers to a pixel in the same row as the first pixel, adjacent to the first pixel, and with a different color. This is because parasitic interference with quantization is usually caused by pixels of different colors in adjacent columns.
[0035] Step 202: Obtain the capacitance influence factor of the pixel array.
[0036] The capacitance influence factor is used to express the impact of parasitic capacitance in a pixel array. In some examples, this capacitance influence factor can be specifically the ratio of parasitic capacitance to design capacitance. For the pixel array currently used in image sensors, both the parasitic capacitance and the design capacitance are known values, meaning the capacitance influence factor is a known value.
[0037] Step 203: Based on the first original quantization value, the second original quantization value, the capacitance influence factor, and the preset correction formula, the first original quantization value is corrected and calculated to obtain the first corrected quantization value.
[0038] The image sensor has a pre-set calibration formula. By substituting the currently obtained first original quantization value, second original quantization value, and capacitance influence factor into this calibration formula for calibration calculation, the first calibrated quantization value can be obtained. This first calibrated quantization value refers to the quantized value of the first pixel after calibration. That is, subsequent image processing will be based on this first calibrated quantization value, rather than the first original quantization value.
[0039] Specifically, the calibration formula differs for different pixel arrays. The image sensor's memory can pre-store calibration formulas corresponding to pixel arrays with different array structures. Therefore, when an image sensor requires calibration of quantized values, it can first determine the array structure used by its pixel array, and then determine the corresponding calibration formula based on that array structure. The derivation process of this calibration formula is explained below:
[0040] Please see Figure 3 , Figure 3 A schematic diagram of the capacitive coupling model between low conversion gain (lcg) nodes and FD nodes in a pixel array is given. Specifically, C1 is C fd +C lcg That is, the equivalent capacitance in LCG mode; C2 is specifically C p, that is, the parasitic capacitance between the lcg node and the FD node.
[0041] For Figure 3 For the FD0 node shown, assume that the injected charge amount is Q0. Since C2 << C1, in the capacitor array on the right side of the FD0 node, C2 in series with C1 is equal to C2, and C2 in parallel with C1 is equal to C1. Based on this, the capacitor array on the right side can be simplified to C2. Thus, it can be known that without considering the coupling effect, the voltage change amount ΔV0 introduced by this FD0 node can be shown as follows:
[0042]
[0043] Then considering the coupling effect of the FD0 node on the FD1 node, it can be known that the voltage change amount ΔV 0-1 coupled from the FD0 node to the FD1 node can be shown as follows:
[0044]
[0045] Similarly, for the FD2 node, assume that the injected charge amount is Q2. It can be known that without considering the coupling effect, the voltage change amount ΔV2 introduced by this FD2 node can be shown as follows:
[0046]
[0047] Then considering the coupling effect of the FD2 node on the FD1 node, it can be known that the voltage change amount ΔV 2-1 coupled from the FD2 node to the FD1 node can be shown as follows:
[0048]
[0049] Similarly, for the FD1 node, assume that the injected charge amount is Q1. It can be known that without considering the coupling effect, the voltage change amount ΔV1 introduced by this FD1 node can be shown as follows:
[0050]
[0051] So far, for the FD1 node, it can be known that its actual total voltage change amount ΔV tot is the combined effect of the charge injection amount and the coupling effect, and can be specifically shown as follows:
[0052]
[0053] However, in the ideal case, there should be no parasitic capacitance between the lcg node and the FD node, that is, C2 does not exist. Therefore, in the ideal case, for the FD1 node, when the injected charge amount is Q1, its ideal total voltage change amount ΔV ideal can be shown as follows:
[0054]
[0055] Therefore, the ideal total voltage change ΔV at node FD1 can be determined. ideal Compared with the actual total voltage change ΔV tot The difference between them is the effect caused by parasitism.
[0056] against Figure 1 For pixel arrays and similar array structures shown, they possess the following characteristics: For any given pixel, the two pixels in adjacent columns are different from that pixel, but these two pixels are identical; that is, in this array structure, for each pixel other than the outermost ring of pixels, when acting as the first pixel, there are second pixels on both its left and right sides, and the colors of these second pixels on both sides are the same. For this, we can set Q1 as Q and C1 as C, then Q0 = Q2 = k1 * Q1 = k1 * Q, C2 = K2 * C1 = k2 * C. Here, K1 is the ratio of photogenerated charges of adjacent pixels of different colors; K2 is the ratio of parasitic capacitance C2 to design capacitance C1, that is, K2 is the capacitance influence factor described above. Therefore, for this array structure, the actual total voltage change ΔV tot It can be simplified to the following formula:
[0057]
[0058] Based on the ideal total voltage change ΔV shown above ideal Compared with the actual total voltage change ΔV tot Since Q / C is voltage, signal quantization directly quantizes the voltage magnitude, thus representing the actual total voltage change ΔV. tot Subtracting the parenthesized part from the formula and multiplying by the coefficient 1 / (1+2k2), the actual total voltage change ΔV can be obtained. tot Restored to the ideal total voltage change ΔV ideal Therefore, the following correction formula can be derived:
[0059]
[0060] Where n is the number of iterations, which is a positive number; it can be understood that the more iterations, the closer the quantization value is to the ideal value, and the higher the accuracy, but at the same time, the computational load will also increase exponentially. x and y represent the quantization values of two different color pixels in adjacent columns. In the scheme proposed in the embodiments of this application, x0 is used to represent the original quantization value of the first pixel, y0 is used to represent the original quantization value of the second pixel, and x n The first corrected quantization value used to represent the first pixel, y nThis is used to represent the second corrected quantization value of the second pixel during the process of correcting the quantization value of the first pixel. In this embodiment, each pixel can be used as the first pixel and the scheme of this embodiment can be executed. That is, the object considered is always the first pixel, so only the calculated x is ultimately considered. n It was output and adopted for use.
[0061] Similarly, for array structures like the Bayer array, they possess the following characteristic: in any two pixels in an adjacent column, one is a pixel of the same color, and the other is a pixel of a different color. Based on this, still setting Q1 as Q and C1 as C, we have k1*Q0=k1*Q1=Q2=k1*Q, C2=K2*C1=k2*C. K1 and K2 have been explained previously and will not be repeated here. Therefore, for this type of array structure, the actual total voltage change ΔV tot It can be simplified to the following formula:
[0062]
[0063] Therefore, the following correction formula can be derived:
[0064]
[0065] Similarly, for array structures like the RGB stripe array, they possess the following characteristics: for any given pixel, the two pixels in its adjacent columns are all different from that pixel, and these two pixels are also distinct from each other; that is, in this type of array structure, each pixel other than the outermost ring of pixels, when used as the first pixel, has a second pixel on both its left and right sides, and the colors of these second pixels on the left and right sides are different. Therefore, for this type of array structure, the following correction formula can be derived:
[0066]
[0067] Where x, y, and z represent the quantization values of three different color pixels in adjacent columns. In the scheme proposed in the embodiments of this application, x0 is used to represent the original quantization value of the first pixel; y0 is used to represent the original quantization value of one of the second pixels (e.g., the second pixel on the left); z0 is used to represent the original quantization value of another second pixel (e.g., the second pixel on the right); x n Used to represent the first corrected quantization value of the first pixel; y n This is used to represent the second corrected quantization value of the corresponding second pixel (e.g., the second pixel on the left) during the process of correcting the quantization value of the first pixel; z nThis is used to represent the second corrected quantization value of the corresponding second pixel (e.g., the second pixel on the right) during the process of correcting the quantization value of the first pixel. In this embodiment, each pixel can be used as the first pixel and the scheme of this embodiment can be executed; that is, the object considered is always the first pixel, so only the calculated x is ultimately considered. n It was output and adopted for use.
[0068] It is understandable that the corresponding correction formulas for various array structures can be obtained through the derivation process shown above, which will not be repeated here.
[0069] In some embodiments, Figure 1 In the array structure shown, each pixel other than the outermost ring of pixels, when used as the first pixel, has a second pixel on both its left and right sides, and the second pixels on both sides have the same color. Image sensors handle this in two ways:
[0070] Method 1: Since the two second pixels have the same color, their coupling effects on the first pixel are similar. Therefore, one of the two second pixels can be randomly selected or selected according to a specified rule as the basis for correction. That is, the second original quantization value, the first original quantization value, and the capacitance influence factor corresponding to the selected second pixel are substituted into the correction formula to calculate the correction of the first original quantization value, thus obtaining the first corrected quantization value. In this way, the image sensor can achieve quantization correction without incurring additional computational burden.
[0071] Method 2: The first original quantization value is corrected and calculated based on each second original quantization value, the first original quantization value, the capacitance influence factor, and the correction formula, resulting in a first candidate corrected quantization value and a second candidate corrected quantization value. That is, the first original quantization value and the capacitance influence factor remain unchanged. The second original quantization values corresponding to the two second pixels are substituted into the correction formula, thus performing two correction calculations for each first pixel to obtain a first candidate corrected quantization value based on one of the second pixels and a second candidate corrected quantization value based on the other second pixel. Then, a weighted average is calculated between the first and second candidate corrected quantization values to obtain the first corrected quantization value. In this way, the image sensor can comprehensively consider the influence of the second pixels on both sides on the first pixel, further improving the quantization correction effect.
[0072] In some embodiments, as described above, the correction formula includes the number of iterations. The more iterations, the closer the quantization value is to the ideal value, and the higher the accuracy, but the computational cost also increases exponentially.
[0073] In response, this application proposes the following methods for setting the number of iterations:
[0074] Setting Method 1: The image sensor is pre-configured with various application scenarios based on image quality requirements, along with target values for the number of iterations corresponding to each scenario. It can be understood that the higher the image quality requirements of a particular application scenario, the larger the target value can be configured for that scenario, thereby improving the image quality obtained in that scenario. Therefore, the image sensor can first determine its current application scenario, then query its configuration information to obtain the target value corresponding to that scenario, and thus set the number of iterations to that target value.
[0075] Method Two: Image sensors are typically integrated into terminal devices, such as cameras, smartphones, or tablets. These devices usually have their own internal processors. For image sensors, this processor is actually an external processor. The external processor can interact with the user, receive relevant configuration information from the user, and then extract content related to the image processor from this configuration information, including but not limited to the target value for the number of iterations. This generates a configuration instruction for the image processor, which is then sent to the image processor. Based on this, the image sensor can set the number of iterations according to the target value carried in the configuration instruction received from the external processor.
[0076] Method 3: The image sensor's own processor can be pre-configured with a default value for the number of iterations. If the image sensor has not been configured with a target value for the number of iterations corresponding to each application scenario, and has not received configuration instructions from an external processor, it can directly set this number of iterations to the default value to ensure that the calibration operation can be performed normally.
[0077] Based on the above-mentioned methods for setting the number of iterations, the image sensor can also propose optimization strategies for the number of iterations. Specifically, after performing correction calculations based on the set number of iterations, feedback information on the correction calculations is received; the number of iterations is then optimized based on the feedback information. In some examples, after performing correction calculations based on the set number of iterations and outputting a specified number of corrected images, the user inputs feedback information on the corrected images. In other examples, the terminal device where the image sensor is located can intelligently analyze the specified number of corrected images, obtain feedback information on the corrected images, and send it to the image sensor. The feedback information may include, but is not limited to, the quality score and output speed score of the corrected images. Based on this feedback information, the image sensor can obtain a comprehensive score for the currently set number of iterations through weighted summation or other methods. If the comprehensive score is higher than a preset first score threshold, the number of iterations can be increased; if the comprehensive score is lower than a preset second score threshold, the number of iterations can be decreased; if the comprehensive score is neither higher than the first score threshold nor lower than the second score threshold, the value of the number of iterations can be maintained.
[0078] As can be seen from the above, the embodiments of this application take into account the influence of parasitic capacitance in the pixel array and the quantization values of adjacent pixels of different colors on quantization, and derive the correction formula in advance through the equivalent circuit of the pixel array. In this way, after the image sensor reads the original quantization value of the pixel array, it can perform correction by traversing the original quantization value of each pixel based on the correction formula. As a result, the image sensor can reduce the quantization interference generated between adjacent color channels, thereby helping to improve the output image quality.
[0079] Corresponding to the correction method provided above, embodiments of this application also provide a correction device. For example... Figure 4 As shown, the correction device 4 includes: a first determining module 401, an acquisition module 402, and a calculation module 403.
[0080] The first determining module 401 is used to determine the first original quantization value of the first pixel and the second original quantization value of the second pixel, wherein the first pixel is any pixel in the pixel array, and the second pixel is a pixel that is in the same row as the first pixel in the pixel array, is adjacent to the first pixel, and has a different color from the first pixel.
[0081] The acquisition module 402 is used to acquire the capacitance influence factor of the pixel array, which is used to express the influence of parasitic capacitance in the pixel array.
[0082] The calculation module 403 is used to perform correction calculation on the first original quantization value based on the first original quantization value, the second original quantization value, the capacitance influence factor and the preset correction formula to obtain the first corrected quantization value. The first corrected quantization value is the quantization value after correction of the first pixel. The correction formula is derived through the equivalent circuit of the pixel array.
[0083] In some embodiments, the correction device 4 further includes:
[0084] The second determining module is used to determine the array structure adopted by the pixel array;
[0085] The third determining module is used to determine the correction formula corresponding to the pixel array based on the array structure.
[0086] In some embodiments, the computing module 403 includes:
[0087] The first calculation unit is used to perform correction calculations on the first original quantization value based on each second original quantization value, the first original quantization value, the capacitance influence factor, and the correction formula when there are two second pixels and the two second pixels have the same color, so as to obtain the first candidate corrected quantization value and the second candidate corrected quantization value.
[0088] The second calculation unit is used to perform a weighted average calculation on the first candidate correction quantization value and the second candidate correction quantization value to obtain the first correction quantization value.
[0089] In some embodiments, the correction formula includes the number of iterations; the correction device 4 further includes:
[0090] The fourth determination module is used to determine the current application scenario of the image sensor;
[0091] The first settings module is used to set the number of iterations according to the application scenario.
[0092] In some embodiments, the correction formula includes the number of iterations; the correction device 4 further includes:
[0093] The second setting module is used to set the number of iterations according to the configuration instructions issued by the external processor.
[0094] In some embodiments, the correction formula includes the number of iterations; the correction device 4 further includes:
[0095] The third setting module is used to set the number of iterations to the default value when no configuration instructions are received from an external processor.
[0096] In some embodiments, the correction device 4 further includes:
[0097] The receiving module is used to receive feedback information on the correction calculation after the correction calculation has been performed based on the set number of iterations.
[0098] The optimization module is used to optimize the number of iterations based on feedback information.
[0099] As can be seen from the above, the embodiments of this application take into account the influence of parasitic capacitance in the pixel array and the quantization values of adjacent pixels of different colors on quantization, and derive the correction formula in advance through the equivalent circuit of the pixel array. In this way, after the image sensor reads the original quantization value of the pixel array, it can perform correction by traversing the original quantization value of each pixel based on the correction formula. As a result, the image sensor can reduce the quantization interference generated between adjacent color channels, thereby helping to improve the output image quality.
[0100] Corresponding to the correction method provided above, this application also provides an image sensor. Please refer to... Figure 5 , Figure 5 A schematic diagram of the image sensor structure is provided. The electronic device 5 includes: a memory 501, a processor 502, and a computer program stored in the memory 501 and executable on the processor. Specifically, the memory 501 stores the computer program, and the processor 502 executes various functional applications and data processing by running the computer program stored in the memory 501 to acquire resources corresponding to preset events. Specifically, the processor 502 performs the following steps by running the computer program stored in the memory 501:
[0101] Determine the first raw quantization value of the first pixel and the second raw quantization value of the second pixel, wherein the first pixel is any pixel in the pixel array, and the second pixel is a pixel that is in the same row as the first pixel in the pixel array, is adjacent to the first pixel, and has a different color from the first pixel;
[0102] Obtain the capacitance influence factor of the pixel array. The capacitance influence factor is used to express the influence of parasitic capacitance in the pixel array.
[0103] The first original quantization value is corrected and calculated based on the first original quantization value, the second original quantization value, the capacitance influence factor, and the preset correction formula to obtain the first corrected quantization value. The first corrected quantization value is the quantization value of the first pixel after correction. The correction formula is derived through the equivalent circuit of the pixel array.
[0104] Assuming the above is the first possible implementation, in the second possible implementation based on the first possible implementation, the processor 502 further performs the following steps when running the computer program stored in the memory 501:
[0105] Determine the array structure used for the pixel array;
[0106] Based on the array structure, the correction formula corresponding to the pixel array is determined.
[0107] In a third possible implementation based on the first possible implementation described above, or based on the second possible implementation described above, when there are two second pixels and the two second pixels have the same color, the first original quantization value is corrected and calculated based on the first original quantization value, the second original quantization value, the capacitance influence factor, and a preset correction formula to obtain the first corrected quantization value, including:
[0108] The first original quantization value is corrected and calculated based on each second original quantization value, the first original quantization value, the capacitance influence factor and the correction formula, respectively, to obtain the first candidate corrected quantization value and the second candidate corrected quantization value.
[0109] The first corrected quantization value is obtained by weighted averaging the first candidate corrected quantization value and the second candidate corrected quantization value.
[0110] In a fourth possible implementation based on the first possible implementation described above, or based on the second possible implementation described above, the correction formula includes the number of iterations; the processor 502 further performs the following steps when running the computer program stored in the memory 501:
[0111] Determine the current application scenarios of the image sensor;
[0112] Set the number of iterations based on the application scenario.
[0113] In a fifth possible implementation based on the first possible implementation described above, or based on the second possible implementation described above, the correction formula includes the number of iterations; the processor 502 further performs the following steps when running the computer program stored in the memory 501:
[0114] Upon receiving configuration instructions from an external processor, the number of iterations is set according to the configuration instructions.
[0115] In a sixth possible implementation based on the first possible implementation described above, or based on the second possible implementation described above, the correction formula includes the number of iterations; the correction method further includes:
[0116] If no configuration instructions are received from an external processor, the number of iterations is set to the default value.
[0117] In a seventh possible implementation provided based on the fourth possible implementation described above, or based on the fifth possible implementation described above and the sixth possible implementation described above, the processor 502 further performs the following steps when running a computer program stored in the memory 501:
[0118] After performing the correction calculation based on the set number of iterations, receive feedback information regarding the correction calculation;
[0119] The number of iterations was optimized based on the feedback information.
[0120] It should be understood that, in the embodiments of this application, the processor 502 may be a central processing unit (CPU), but it may also be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor.
[0121] Memory 501 may include read-only memory and random access memory, and provides instructions and data to processor 502. Some or all of memory 501 may also include non-volatile random access memory. For example, memory 501 may also store device category information.
[0122] As can be seen from the above, the embodiments of this application take into account the influence of parasitic capacitance in the pixel array and the quantization values of adjacent pixels of different colors on quantization, and derive the correction formula in advance through the equivalent circuit of the pixel array. In this way, after the image sensor reads the original quantization value of the pixel array, it can perform correction by traversing the original quantization value of each pixel based on the correction formula. As a result, the image sensor can reduce the quantization interference generated between adjacent color channels, thereby helping to improve the output image quality.
[0123] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the above device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit. Furthermore, the specific names of the functional units and modules are only for easy differentiation and are not intended to limit the scope of protection of this application. The specific working process of the units and modules in the above system can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.
[0124] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.
[0125] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of external device software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.
[0126] In the embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the system embodiments described above are merely illustrative. For instance, the division of modules or units described above is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection between devices or units through some interfaces, and may be electrical, mechanical, or other forms.
[0127] The units described above as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.
[0128] If the integrated units described above are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments can also be implemented by a computer program instructing associated hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable storage medium can include: any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer-readable storage device, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium, etc. It should be noted that the contents of the aforementioned computer-readable storage media may be appropriately added to or subtracted from the contents according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable storage media may not include electrical carrier signals and telecommunication signals.
[0129] The above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.
Claims
1. A calibration method, characterized in that, include: Determine the first raw quantization value of the first pixel and the second raw quantization value of the second pixel, wherein the first pixel is any pixel in the pixel array, and the second pixel is a pixel that is in the same row of the pixel array as the first pixel, is adjacent to the first pixel, and has a different color from the first pixel; Obtain the capacitance influence factor of the pixel array, which is used to express the influence of parasitic capacitance in the pixel array; The first original quantization value is corrected and calculated based on the first original quantization value, the second original quantization value, the capacitance influence factor, and the preset correction formula to obtain the first corrected quantization value. The first corrected quantization value is the quantization value of the first pixel after correction. The correction formula is derived through the equivalent circuit of the pixel array.
2. The correction method as described in claim 1, characterized in that, The correction method further includes: Determine the array structure used by the pixel array; Based on the array structure, the correction formula corresponding to the pixel array is determined.
3. The correction method as described in claim 1 or 2, characterized in that, When two second pixels exist and the two second pixels have the same color, the step of correcting the first original quantization value based on the first original quantization value, the second original quantization value, the capacitance influence factor, and a preset correction formula to obtain a first corrected quantization value includes: The first original quantization value is corrected and calculated based on each of the second original quantization value, the first original quantization value, the capacitance influence factor, and the correction formula to obtain the first candidate corrected quantization value and the second candidate corrected quantization value. The first corrected quantized value is obtained by performing a weighted average calculation on the first candidate corrected quantized value and the second candidate corrected quantized value.
4. The correction method as described in claim 1 or 2, characterized in that, The correction formula includes the number of iterations; the correction method further includes: Determine the current application scenarios of the image sensor; The number of iterations is set according to the application scenario.
5. The correction method as described in claim 1 or 2, characterized in that, The correction formula includes the number of iterations; the correction method further includes: Upon receiving a configuration instruction from an external processor, the iteration number is set according to the configuration instruction.
6. The correction method as described in claim 1 or 2, characterized in that, The correction formula includes the number of iterations; the correction method further includes: If no configuration instructions are received from an external processor, the number of iterations is set to the default value.
7. The correction method according to any one of claims 4 to 6, characterized in that, The correction method further includes: After performing the correction calculation based on the set number of iterations, receive feedback information regarding the correction calculation; The number of iterations is optimized based on the feedback information.
8. A calibration device, characterized in that, include: The first determining module is used to determine the first original quantization value of the first pixel and the second original quantization value of the second pixel, wherein the first pixel is any pixel in the pixel array, and the second pixel is a pixel that is in the same row of the pixel array as the first pixel, adjacent to the first pixel, and has a different color from the first pixel. The acquisition module is used to acquire the capacitance influence factor of the pixel array, wherein the capacitance influence factor is used to express the influence of parasitic capacitance in the pixel array; The calculation module is used to perform correction calculation on the first original quantization value based on the first original quantization value, the second original quantization value, the capacitance influence factor and the preset correction formula to obtain a first corrected quantization value. The first corrected quantization value is the quantization value after correction of the first pixel. The correction formula is derived through the equivalent circuit of the pixel array.
9. An image sensor, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the method as described in any one of claims 1 to 7.
10. A computer program product, characterized in that, The computer program product includes a computer program that, when executed by one or more processors, implements the method as described in any one of claims 1 to 7.