A method, device and storage medium for evaluating performance of an image acquisition module

Abstract

Embodiments of the present application provide a method and device for evaluating performance of an image acquisition module, and a storage medium, wherein the method for evaluating performance of an image acquisition module comprises: obtaining an evaluation image; removing a direct current component included in the evaluation image to obtain a first image; obtaining signal amplitudes of at least some pixel points on the first image; and calculating a signal-to-noise ratio of the image acquisition module to be evaluated according to the signal amplitudes. Some embodiments of the present application use techniques such as direct current removal and envelope extraction, which can effectively reduce the influence of noise on the signal amplitudes, make the estimation of the signal amplitudes and the signal-to-noise ratio more accurate, and further improve the evaluation accuracy of the performance of the module.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of image acquisition module performance evaluation, in particular, the embodiments of the present application relate to a method and device for evaluating the performance of an image acquisition module, and a storage medium. BACKGROUND

[0002] The signal-to-noise ratio is the most important indicator for evaluating the sensitivity of an image acquisition module, and is usually defined as the ratio of signal power to noise power, and is usually expressed in decibels to avoid excessively large values and facilitate comparison. In order to facilitate calculation, the formula for calculating the signal-to-noise ratio is generally defined as the ratio of signal amplitude to noise amplitude.

[0003] However, the signal amplitude obtained by using the traditional method carries more noise, so the signal-to-noise ratio calculated is also greatly affected by noise, and the performance of the image acquisition module cannot be accurately evaluated. SUMMARY

[0004] The embodiments of the present application aim to provide a method and device for evaluating the performance of an image acquisition module, and some embodiments of the present application use techniques such as removing direct current and taking envelope to effectively reduce the influence of noise on signal amplitude, making the estimation of signal amplitude and signal-to-noise ratio more accurate, and facilitating subsequent evaluation of the performance of the module.

[0005] In a first aspect, some embodiments of the present application provide a method for evaluating the performance of an image acquisition module, the method comprising: obtaining an evaluation image, wherein the evaluation image is obtained by using an image acquisition module to image a test pattern; removing direct current components included in the evaluation image to obtain a first image; obtaining signal amplitudes of at least some pixel points on the first image; and calculating a signal-to-noise ratio of the image acquisition module to be evaluated based on the signal amplitudes.

[0006] Some embodiments of the present application effectively reduce the noise signals carried in the signal amplitudes by removing direct current, and thus can improve the accuracy of the signal-to-noise ratio calculated based on the signal amplitudes, so as to more accurately reflect the performance of the image acquisition module to be evaluated.

[0007] In some embodiments, the removing of the direct current components included in the evaluation image to obtain the first image comprises: obtaining values of the direct current components of each pixel point on the evaluation image; and for each pixel point on the evaluation image, subtracting the value of the corresponding direct current component from the pixel value to obtain the first image.

[0008] Some embodiments of the present application provide a method for removing direct current components, i.e. obtaining a first image of the same size as the evaluation image by subtracting the direct current components from each pixel point on the evaluation image, thereby improving the accuracy of the obtained signal amplitudes.

[0009] In some embodiments, the acquiring the DC component of each pixel point on the evaluation image comprises: performing mean filtering on a plurality of pixel values in a sliding window corresponding to the pixel point on the evaluation image to obtain the value of the DC component of the pixel point.

[0010] Some embodiments of the present application acquire the DC component of each pixel point through a mean filtering algorithm and a sliding window, thereby improving the accuracy of the acquired DC component.

[0011] In some embodiments of the present application, the test pattern comprises a stripe pattern or a chessboard pattern, wherein the evaluation image is an image obtained by photographing the test pattern, or the evaluation image is an average image obtained by averaging the pixel values of the same pixel points on a plurality of images, and the plurality of images are a plurality of images obtained by performing image acquisition on the test pattern a plurality of times by using the image acquisition module.

[0012] Some embodiments of the present application can effectively avoid the technical problem of inconvenient evaluation image acquisition caused by using a finger to collect a fingerprint image by performing image acquisition on a stripe to evaluate the performance of the image acquisition module.

[0013] In some embodiments, the signal amplitude is represented by an envelope value.

[0014] In some embodiments, the acquiring the signal amplitude of at least part of the pixel points on the first image comprises: determining the envelope value of each pixel point in the at least part of the pixel points according to the positive and negative characteristics of the pixel values of the at least part of the pixel points on the first image.

[0015] Some embodiments of the present application determine the envelope value of each pixel point according to the positive and negative of the amplitude on the corresponding image after removing the DC component, thereby accurately representing the intensity of the fingerprint signal.

[0016] In some embodiments, the determining the envelope value of each pixel point in the at least part of the pixel points according to the positive and negative characteristics of the pixel values of the at least part of the pixel points on the first image comprises: if the sign of the pixel value of a first pixel point in the at least part of the pixel points is positive, taking the absolute value of the maximum pixel value in the adjacent region of the first pixel point on the first image as the envelope value of the first pixel point; if the sign of the pixel value of a second pixel point in the at least part of the pixel points is negative, taking the absolute value of the minimum pixel value in the adjacent region of the second pixel point on the first image as the envelope value of the pixel point; or if the value of a third pixel point in the at least part of the pixel points is zero, the envelope value of the third pixel point is zero; wherein the adjacent region is a region defined by a sliding window.

[0017] Some embodiments of the present application determine the corresponding envelope value by the pixel value of any pixel point adjacent to the pixel point and the symbol of the pixel point, thereby improving the accuracy of envelope value calculation.

[0018] In some embodiments, the evaluation image is obtained by the image acquisition module capturing an image of the film with the test pattern illuminated by the light source under test; the evaluation image is obtained by the image acquisition module capturing an image of a rubber test head with a first display screen spaced from the image acquisition module, wherein the rubber test head has the test pattern on one side close to the first display screen; or the evaluation image is obtained by the image acquisition module capturing an image of the test pattern displayed by the second display screen.

[0019] Some embodiments of the present application can avoid the technical problem of complicated image acquisition caused by repeatedly pressing the image acquisition module by the film or other means to take the test stripes.

[0020] In some embodiments, before the signal amplitude is used to calculate the signal-to-noise ratio of the image acquisition module, the method further comprises: obtaining the noise amplitude of each pixel point in the at least part of the pixel points; wherein the signal amplitude is used to calculate the signal-to-noise ratio of the image acquisition module, including: calculating the signal-to-noise ratio according to the signal amplitude and the signal-to-noise ratio calculation formula, wherein the signal-to-noise ratio calculation formula is related to the signal amplitude and the noise amplitude of each pixel point in the at least part of the pixel points.

[0021] Some embodiments of the present application calculate the signal-to-noise ratio according to the signal amplitude and the noise amplitude.

[0022] In some embodiments, the noise amplitude of each pixel point in the at least part of the pixel points is obtained by multiple images, wherein the multiple images are obtained by the image acquisition module capturing multiple images of the test pattern.

[0023] Some embodiments of the present application obtain the noise amplitude by multiple images, thereby improving the accuracy of the obtained noise amplitude.

[0024] In some embodiments, the number of the multiple images is L, L is an integer greater than 1, wherein the noise amplitude is obtained by calculating the standard deviation of the L frames of each pixel point.

[0025] Some embodiments of the present application obtain the noise amplitude of each pixel point by standard deviation, thereby improving the speed of data processing.

[0026] In some embodiments, the number of the plurality of images is L, L is an integer greater than 1, and the noise amplitude is obtained from the plurality of images by taking the root mean square error between any one of the L frames of images and the evaluation image as the noise amplitude of each pixel point, where the evaluation image is an image obtained by averaging the pixel values of each pixel point in the L frames of images.

[0027] Some embodiments of the present application improve the accuracy of the noise amplitude by calculating the noise amplitude of each pixel point by root mean square error.

[0028] In some embodiments, the signal-to-noise ratio is calculated by the following formula:

[0029]

[0030] where i and j are the coordinates of each pixel point in the target region, the target region is a region defined by the at least part of the pixel points, S ij represents the signal amplitude of the pixel point with coordinates i and j, N ij represents the noise amplitude of the pixel point with coordinates i and j.

[0031] Some embodiments of the present application obtain the signal-to-noise ratio of the image acquisition device to be evaluated by calculating the signal-to-noise ratio of part or all of the pixel points in the evaluation image.

[0032] In some embodiments, after calculating the signal-to-noise ratio of the image acquisition module to be evaluated according to the signal amplitude and signal-to-noise ratio calculation formula, the method further comprises evaluating the performance of the image acquisition module to be evaluated according to the signal-to-noise ratio.

[0033] Some embodiments of the present application further determine whether the image acquisition device to be evaluated meets the quality requirements according to the calculated signal ratio.

[0034] In some embodiments, the signal-to-noise ratio of the image acquisition module to be evaluated is represented by the at least part of the pixel points.

[0035] In the second aspect, some embodiments of the present application provide a device for evaluating the performance of an image acquisition module, the device comprising: an evaluation image acquisition module configured to acquire an evaluation image, where the evaluation image is an image obtained by image acquisition of a test pattern by an image acquisition module; a direct current component removal module configured to remove the direct current component included in the evaluation image to obtain a first image; a signal amplitude acquisition module configured to acquire the signal amplitude of at least part of the pixel points in the first image; and a signal-to-noise ratio acquisition module configured to calculate the signal-to-noise ratio of the image acquisition module to be evaluated according to the signal amplitude.

[0036] In a third aspect, some embodiments of the present application provide a readable storage medium having a program stored thereon, where the program, when executed by a processor, can implement the method of the first aspect.

[0037] In a fourth aspect, some embodiments of the present application provide an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, where the processor, when executing the program, can implement the method of the first aspect. BRIEF DESCRIPTION OF DRAWINGS

[0038] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the drawings needed to be used in the embodiments of the present application. It should be understood that the following drawings only show some of the embodiments of the present application, and therefore should not be regarded as a limitation on the scope, and for the ordinary skilled in the art, other related drawings can also be obtained without creative labor on the basis of these drawings.

[0039] Figure 1 The composition schematic diagram of the system for evaluating the performance of the image acquisition module provided by the embodiments of the present application;

[0040] Figure 2 The flowchart of the method for evaluating the performance of the image acquisition module provided by the embodiments of the present application;

[0041] Figure 3 The test stripe schematic diagram provided by the embodiments of the present application;

[0042] Figure 4 One of the scenes for acquiring the texture image provided by the embodiments of the present application;

[0043] Figure 5 The second scene for acquiring the texture image provided by the embodiments of the present application;

[0044] Figure 6 The third scene for acquiring the texture image provided by the embodiments of the present application;

[0045] Figure 7 The composition block diagram of the device for evaluating the performance of the image acquisition module provided by the embodiments of the present application;

[0046] Figure 8 The composition schematic diagram of the electronic device provided by the embodiments of the present application. DETAILED DESCRIPTION

[0047] The technical solutions of the embodiments of the present application will be described below in combination with the drawings in the embodiments of the present application.

[0048] It should be noted that similar reference numerals and letters refer to like items in the accompanying drawings, and that, once an item is defined in one drawing, it should not require further definition and explanation in subsequent drawings. Also, in the description of the present application, the terms "first", "second", and the like are used only to distinguish descriptions, and should not be understood as indicating or implying relative importance. Some of the images in the following examples are obtained by directly capturing images of the patterns by the image capturing module, and some of the images are obtained by calculating based on the images taken.

[0049] Please refer to Figure 1 , Figure 1 The schematic diagram of the system 100 for evaluating the performance of the image capturing module provided by some embodiments of the present application.

[0050] Figure 1 The system 100 for evaluating the performance of the image capturing module provided by some embodiments of the present application includes the image capturing module 10 to be evaluated for taking one or more images, and the server 20 for obtaining the signal-to-noise ratio or quality of the image capturing module to be evaluated according to the evaluation image.

[0051] In some embodiments of the present application, Figure 1 The image capturing module 10 to be evaluated directly sends the captured image to the server 20, and then the server 20 takes the image as the evaluation image, and further obtains the signal-to-noise ratio of the image capturing module to be evaluated according to the evaluation image. For example, in some embodiments of the present application, the server 20 obtains the signal amplitude by taking the envelope of the direct current of the evaluation image, and then obtains the signal-to-noise ratio of the image capturing module to be evaluated according to the signal amplitude and the signal-to-noise ratio calculation formula.

[0052] In some embodiments of the present application, Figure 1 The image capturing module 10 to be evaluated directly sends the captured image to the server 20, and then the server 20 takes the image as the evaluation image, and further obtains the signal-to-noise ratio of the image capturing module to be evaluated according to the evaluation image. For example, in some embodiments of the present application, the server 20 obtains the signal amplitude by taking the envelope of the direct current of the evaluation image, and then obtains the signal-to-noise ratio of the image capturing module to be evaluated according to the signal amplitude and the signal-to-noise ratio calculation formula.

[0053] In some embodiments of the present application, Figure 1The evaluation image acquisition module 10 has signal processing capability to process the collected multiple images (or multiple frames of images) to obtain an evaluation image, and send the evaluation image to the server 20, and then the server 20 obtains the signal-to-noise ratio of the evaluation image acquisition module according to the evaluation image. For example, in some embodiments of the present application, the server 20 obtains the signal amplitude of the evaluation image by using the method of removing direct current and taking envelope, and then obtains the signal-to-noise ratio of the evaluation image acquisition device according to the signal amplitude and the signal-to-noise ratio calculation formula.

[0054] In some embodiments of the present application, the evaluation image is an average texture image obtained by averaging the pixel values of each pixel point on multiple images, and the multiple images are multiple frames of images obtained by multiple times of shooting the test stripes or skin texture by using the evaluation image acquisition module. For example, in some embodiments, the multiple images for obtaining the average texture image are N frames of images (i.e. Figure 1 the first frame of image 101, the second frame of image 102, the third frame of image 103, the fourth frame of image 104, …, and the Nth frame of image) obtained by continuously collecting images with a fixed exposure time of the evaluation image acquisition module, where N is an integer greater than 1. In some embodiments of the present application, the process of obtaining the evaluation image from the N frames of images includes: obtaining N pixel values corresponding to a first pixel point (belonging to any one pixel point on the image) from the N frames of images, and solving the average value of the N pixel values to obtain the average pixel value of the first pixel point. In this way, the average pixel values of all pixel points are obtained, and the average texture image is obtained, which can be used as the evaluation image.

[0055] It should be noted that, Figure 1 The process of removing direct current and taking envelope of the evaluation image performed by the server 20 can also be performed by the evaluation image acquisition module 10 or by the mobile phone. That is, in some embodiments of the present application, a microprocessor is integrated in the evaluation image acquisition module 10 or the mobile phone, and the microprocessor can obtain the signal-to-noise ratio of the module according to the evaluation image. It can be understood that in these embodiments, the processor of the mobile phone reads one image or multiple images collected by the evaluation image acquisition module 10 from the register through the bus, and then evaluates the performance of the image acquisition module based on the read images.

[0056] It can be understood that, Figure 1 The evaluation image acquisition module includes an under-screen fingerprint image acquisition module or other types of image acquisition modules, and the embodiments of the present application do not limit the specific type of the evaluation image acquisition module 10.

[0057] The following will be described in combination with Figure 2 the evaluation image acquisition module 10 is an under-screen fingerprint image acquisition module. Figure 1The method for evaluating the performance of an image acquisition module is executed by the server 20 or by the microprocessor integrated within the image acquisition module 10 itself.

[0058] like Figure 2 As shown, some embodiments of this application provide a method for evaluating the performance of an image acquisition module. The method includes: S101, acquiring an evaluation image, wherein the evaluation image is obtained by acquiring a test pattern using an image acquisition module; S102, removing the DC component from the evaluation image to obtain a first image; S103, acquiring the signal amplitude values ​​of at least a portion of the pixels in the first image; and S104, calculating the signal-to-noise ratio of the image acquisition module to be evaluated based on the signal amplitude values.

[0059] It is understood that, prior to S101, some embodiments of this application of the method for evaluating the performance of an image acquisition module further include the process of acquiring one or more images containing a test pattern using the image acquisition module to be evaluated.

[0060] The above process is illustrated below by example.

[0061] Combination Figures 3-6 This example illustrates the process of acquiring one or more images using an image acquisition module. It should be noted that the types of test patterns include: striped patterns (e.g., alternating black and white vertical stripes), checkerboard patterns, or patterns with multiple nested rings, etc. The embodiments of this application do not limit the specific type of test pattern. For example, Figure 3 The diagram shows a test stripe pattern. It is understood that some embodiments of this application utilize the image acquisition module to be evaluated. Figure 3 The test stripe pattern is used to acquire images, resulting in one or more images including the test pattern. The following provides a combination of... Figures 4-6 Three examples illustrate the application of... Figure 3 The method of image acquisition for testing stripe patterns.

[0062] like Figure 4 As shown, the texture image in this figure was obtained by the image acquisition module 10 to be evaluated from an image of a film with test stripes illuminated by the test light source. From... Figure 4 It can be seen that the film includes Figure 3 The test stripes. It should be noted that... Figure 4 The light emitted by the bulb is used as the test light source, but some embodiments of this application do not limit the specific type of test light source. For example, in some embodiments of this application, a surface light source can also be used. Figure 4 The test light source. If multiple texture images are needed, only control... Figure 4The image acquisition module 10 to be evaluated continuously captures multiple frames of images on the film with test stripes under the same exposure time.

[0063] like Figure 5 As shown, in Figure 5 From left to right, the image shows the under-display module, the device screen, and rubber test points, with test patterns displayed on the rubber test points. Figure 5 The image of the test pattern is obtained through the image acquisition module 10 to be evaluated and the first display screen (i.e., the image acquisition module to be evaluated is spaced apart from the image acquisition module to be evaluated) Figure 5 The image is obtained by capturing images using a rubber test head (the device screen), wherein the side of the rubber test head closest to the first display screen has, as shown in the image... Figure 3 The test stripes are shown. For example, in some embodiments, the image acquisition module to be evaluated is an under-screen skin texture acquisition module, then... Figure 5 The first display screen is the display screen when the image acquisition module to be evaluated is used as an under-display fingerprint recognition module.

[0064] like Figure 6 As shown, the texture image of this figure is obtained by the image acquisition module 10 to be evaluated from the display screen (i.e., Figure 6 The image is obtained by capturing test stripes displayed on the device screen. In some embodiments, the image acquisition module 10 to be evaluated is an under-display fingerprint acquisition module. Figure 6 The display screen is the corresponding display screen.

[0065] It is understood that those skilled in the art can use different methods to acquire evaluation images with test patterns (e.g., test stripes) depending on the different generation stages and environments of different fingerprint recognition modules. For example, in some embodiments of this application, a display screen is used to acquire images of test stripes, while in other embodiments of this application, a display screen is not required when the module to be evaluated is used to capture images of the test stripes.

[0066] In some embodiments of this application, for example, the chart (i.e., an example of a test pattern) is placed directly on the lens for imaging, with the patterned side of the chart facing down and a flesh-colored rubber tip placed on it. In some embodiments, after each image is captured, the chart may need to be repositioned on the screen at a different angle. This imaging operation is repeated to capture multiple texture images from different angles.

[0067] It should be noted that the fixed exposure mode is used to collect one data at a time when collecting the image by using the above-mentioned manner, and the exposure time of the image collection module 10 to be evaluated is fixed according to the collection requirement. In some embodiments of the present application, the image taken by the image collection module to be evaluated is a gray-scale image, and the corresponding pixel value is a gray-scale value on the gray-scale image. When a plurality of images are obtained by using the above-mentioned manner, the average pixel value of each point is obtained by solving the average value of all pixel values of the same pixel point on the plurality of images, and the evaluation image is obtained. In some embodiments of the present application, the fingerprint identification module to be evaluated is an RGB color module, and the corresponding evaluation image can be a gray-scale image selected from one of the RGB three channels. In some embodiments of the present application, the RGB three channels are processed respectively, and the final result is obtained according to the three results, for example, the minimum or maximum or weighted average is selected.

[0068] That is, the evaluation image involved in S101 is an image in some embodiments, and the evaluation image is an average image obtained by averaging the pixel values of each pixel point on the plurality of images taken in another embodiment.

[0069] For example, in some embodiments of the present application, the test pattern is a black-and-white interval vertical stripe, and S101 collects the image of the black-and-white interval vertical stripe pattern by using the image collection module to be evaluated, obtains an image containing the pattern, and takes the image as the evaluation image. That is, the signal-to-noise ratio of the image collection module to be evaluated can be obtained based on the black-and-white interval vertical stripe image.

[0070] For example, in some embodiments of the present application, the test pattern is a black-and-white interval vertical stripe, and S101 collects the image of the black-and-white interval vertical stripe pattern by using the image collection module to be evaluated, obtains an image containing the pattern, and takes the image as the evaluation image. That is, the signal-to-noise ratio of the image collection module to be evaluated can be obtained based on the black-and-white interval vertical stripe image.

[0071] For example, in some embodiments of the present application, the evaluation image involved in S101 is a texture image obtained by capturing the test stripe or skin texture using the image acquisition module to be evaluated. In some other embodiments of the present application, the evaluation image involved in S102 is an average texture image obtained by averaging the pixel values of each pixel point on multiple texture images, and the multiple texture images are obtained by capturing the test stripe or skin texture multiple times using the image acquisition module to be evaluated.

[0072] In some embodiments of the present application, S102 comprises: obtaining the value of the DC component of each pixel point on the evaluation image; for each pixel point on the evaluation image, subtracting the value of the corresponding DC component from the pixel value to obtain the first image. For example, in some embodiments of the present application, the process of obtaining the value of the DC component of each pixel point on the evaluation image involved in S102 comprises: performing mean filtering on the multiple pixel values in the sliding window corresponding to any pixel point on the evaluation image to obtain the DC component of the any pixel point.

[0073] It can be understood that, in some embodiments of the present application, the pixel values of each pixel point on the evaluation image are represented by a matrix (i.e. each element in the matrix is the pixel value of the corresponding pixel point), and the DC component values of each pixel point are also represented by a matrix (i.e. each element in the matrix is the value of the DC component of the corresponding pixel point), and S102 comprises: subtracting the matrix corresponding to the evaluation image from the matrix corresponding to the DC component to obtain the first image after DC removal. For example, for the first pixel point, the pixel value of the first pixel point on the first image is obtained by subtracting the value of the DC component of the first pixel point from the pixel value of the first pixel point on the evaluation image.

[0074] It should be noted that the DC component determines the average value of the signal within a certain range, and in some embodiments of the present application, the DC component is estimated by the average value of the pixel values of each pixel point within a certain range. S102 can obtain the noise signal carried in the signal amplitude by obtaining the value of the DC component of each pixel point, and some embodiments of the present application effectively reduce the noise signal carried in the signal amplitude by DC removal, thereby improving the accuracy of the signal-to-noise ratio calculated according to the signal amplitude, so as to more accurately reflect the performance of the image acquisition module to be evaluated.

[0075] In some embodiments of the present application, the test pattern is a stripe pattern or a skin texture pattern, and it can be understood that the size of the sliding window involved in S102 needs to be able to contain at least the valley and ridge of a pair of stripes in the stripe pattern.

[0076] In some embodiments of the present application, the signal amplitude involved in S103 is characterized by an envelope value. That is, the signal amplitude of each pixel point is characterized by the envelope intensity of the pixel point. It can be understood that the envelope value or envelope intensity is used to characterize the signal intensity at the position of the corresponding pixel point.

[0077] In some embodiments of the present application, S103 comprises: determining the envelope value of each pixel point in the at least partial pixel points according to the positive and negative characteristics of the pixel value of the pixel point on the first image.

[0078] For example, in some embodiments of the present application, S103 comprises: if the sign of the pixel value of a first pixel point in the at least partial pixel points is positive, taking the absolute value of the maximum pixel value in the adjacent region of the first pixel point on the first image as the envelope value of the first pixel point; if the sign of the pixel value of a second pixel point in the at least partial pixel points is negative, taking the absolute value of the minimum pixel value in the adjacent region of the second pixel point on the first image as the envelope value of the second pixel point; or if the value of a third pixel point in the at least partial pixel points is zero, the envelope value of the third pixel point is zero; wherein the adjacent region is a region defined by a sliding window.

[0079] It should be noted that the first pixel point, the second pixel point and the third pixel point are not specific to a certain pixel point, but for the convenience of description, these pixel points belong to any one of the at least partial pixel points.

[0080] For example, in some embodiments of the present application, S103 comprises: determining the envelope value of each pixel point in the partial pixel points according to the positive and negative characteristics of the pixel value of the pixel point on the first image, and correspondingly obtaining the noise amplitude of the partial pixel points in the subsequent process, and then obtaining the signal-to-noise ratio of the partial pixel points according to the ratio of the signal amplitude to the noise amplitude of the partial pixel points. That is, in these embodiments, the performance of the image acquisition module to be evaluated is reflected by the signal-to-noise ratio of the partial pixel points.

[0081] For example, in some embodiments of the present application, S103 comprises: determining the envelope value of each pixel point on the first image obtained after removing the direct current from the evaluation image according to the positive and negative characteristics of the pixel value of the pixel point on the first image, and correspondingly obtaining the noise amplitude of all the pixel points in the subsequent process, and then obtaining the signal-to-noise ratio of the entire image according to the ratio of the signal amplitude to the noise amplitude of all the pixel points. That is, in these embodiments, the performance of the image acquisition module to be evaluated is reflected by the signal-to-noise ratio of all the pixel points on the acquired image.

[0082] It is understood that, in some embodiments of this application, in order to determine the signal-to-noise ratio (SNR) according to the SNR calculation formula, the method for evaluating the performance of the image acquisition module further includes: obtaining the noise amplitude of each pixel in the at least some pixel points, wherein the SNR calculation formula is related to the signal amplitude and noise amplitude of each pixel in the at least some pixel points. For example, in some embodiments of this application, the noise amplitude of each pixel in the at least some pixel points is obtained from multiple images.

[0083] The noise amplitude can be obtained based on a single image or multiple images, where multiple images are obtained by the image acquisition module performing multiple image acquisitions on the test pattern. It should be noted that using multiple images to obtain the noise amplitude of each pixel can include various examples. For instance, some embodiments of this application obtain the noise amplitude by calculating the standard deviation of each pixel's variation over L frames, while other embodiments may use the root mean square error to estimate the noise amplitude.

[0084] The following two examples illustrate the method for calculating the noise amplitude of each pixel based on multiple images.

[0085] For example, in some embodiments of this application, the number of multi-frame images for obtaining noise amplitude is L (i.e., from...). Figure 1 The image acquisition module to be evaluated continuously captures L frames of images, where L is an integer greater than 1, and the noise amplitude of each pixel is obtained by calculating the standard deviation of the change of each pixel in L frames.

[0086] For example, in some embodiments of this application, the number of multi-frame images for obtaining noise amplitude is L (i.e., from...). Figure 1 The evaluation image is obtained by continuously capturing L frames of images (where L is an integer greater than 1) using an image acquisition module to be evaluated. S101 involves calculating the average value of the same pixels in the L frames. S103 involves obtaining the noise amplitude of each pixel in the test image, which includes, for example, using the root mean square error between any frame in the L frames and the evaluation image as the noise amplitude of each pixel. The evaluation image is obtained by averaging the pixel values ​​of each pixel in the L frames. For example, if the test pattern is a striped pattern, the evaluation image is obtained by calculating the average value of each pixel in the L frames obtained from capturing the striped pattern, including using the root mean square error between any frame in the L frames and the evaluation image as the noise amplitude of each pixel. It is understood that the noise amplitude of each pixel obtained in this way is the same.

[0087] As described above, S103 calculates the signal-to-noise ratio by the signal-to-noise ratio formula. It can be understood that the signal-to-noise ratio, English name called SNR or S / N (SIGNAL-NOISE RATIO), also known as signal-to-noise ratio, refers to the proportion of signal and noise in an electronic device or electronic system. The signal here refers to the electronic signal (for example, the evaluation image obtained based on the collected test pattern) from the outside of the device which needs to be processed by the device, and the noise refers to the irregular additional signal in the original signal after the device, and the signal does not change with the change of the original signal.

[0088] In some embodiments of the present application, in order to avoid the signal-to-noise ratio value being too large, a logarithmic calculation of the signal-to-noise ratio is introduced, and the signal-to-noise ratio calculation formula is as follows:

[0089]

[0090] Wherein, i and j are the coordinates of each pixel point in the target area in the target area, the target area is a region defined by the at least part of the pixel points, S ij The signal amplitude corresponding to the pixel point with coordinates i and j is represented by S(i, j). ij The noise amplitude corresponding to the pixel point with coordinates i and j is represented by N(i, j).

[0091] It should be noted that in order to obtain the signal-to-noise ratio, when the signal amplitude obtained is the amplitude of part of the pixel points, the noise amplitude obtained is also the noise amplitude of part of the pixel points; when the signal amplitude obtained is the amplitude of all the pixel points on the image, the noise amplitude obtained is also the noise amplitude of all the pixel points.

[0092] In order to be able to judge whether the quality of the image acquisition module to be evaluated meets the standard according to the signal-to-noise ratio, after S104, the method for evaluating the performance of the image acquisition module further comprises: evaluating the performance of the image acquisition module to be evaluated according to the signal-to-noise ratio. For example, in some embodiments, whether the quality of the image acquisition module to be evaluated meets the standard is determined according to whether the signal-to-noise ratio is greater than a set threshold. For example, when the signal-to-noise ratio is less than the set threshold, it is considered that the quality of the image acquisition module to be evaluated does not meet the factory requirements, otherwise it meets the factory requirements.

[0093] It should be noted that some embodiments of the present application can also be used to evaluate the signal-to-noise ratio of the fingerprint image taken by the fingerprint identification module under the screen, and then determine whether the fingerprint image continues to input the identification module for identity recognition or anti-fake identification according to the judgment result.

[0094] As can be understood from the above description, the signal-to-noise ratio of the image acquisition module to be evaluated can be represented by all pixel points or by part of the pixel points.

[0095] The following uses a specific example to elaborate on the method for evaluating the performance of the image acquisition module in some embodiments of the present application.

[0096] Example 1

[0097] The first step is for Figure 1 the image acquisition module to be evaluated to capture a grayscale image A (i.e., the evaluation image). This grayscale image is represented by the following matrix, where each element in the matrix represents the pixel value of the corresponding pixel point:

[0098]

[0099] The second step is to select the sliding window parameter R, and calculate the DC component of the corresponding pixel point within the ranges defined by the sliding window through the mean filtering algorithm (Box Filter).

[0100] Suppose the DC components of the calculated pixel points are represented by the following matrix D:

[0101]

[0102] Where: |i - x| ≤ R and |j - y| ≤ R. The symbol “overline” (read as “bar”) represents taking the average. In the above formula, A ij overline represents the average of all (2R + 1) * (2R + 1) pixel points in the rectangular area composed of R pixel points in each of the upper, lower, left, and right directions of the pixel point with coordinates (x, y) on the grayscale image in the first step. ij of A ij is the pixel value of the element in the i-th row and j-th column of the evaluation image. For example, when R = 2, it is a window range from two rows above the current analyzed pixel point to two rows below, and from two columns to the left to two columns to the right. That is, R = 2 corresponds to two rows and two columns. In addition to the rows counted up, down, left, and right, it also includes the row and column where the current analyzed pixel point itself is located, and the number of pixels in this window is 5 * 5, where 2R + 1 = 5.

[0103] The third step is to subtract the matrix corresponding to the grayscale image from the matrix corresponding to the DC component to obtain the first image A' after removing the DC component. Here, the first image A' is represented by the arithmetic operation: A' = A - D.

[0104] The fourth step is to calculate the envelope height based on the (positive or negative) sign of the pixel value of each pixel point on the first image A' after removing the DC component, and obtain the matrix S:

[0105]

[0106] Where, A'ij is the pixel value of the element in the i-th row and j-th column on the first image.

[0107] It should be noted that in some embodiments of the present application, each element in the matrix S is used as the signal amplitude of the evaluation image A at the corresponding coordinates for the calculation of the signal-to-noise ratio.

[0108] It can be understood that the signal-to-noise ratio of all pixel points can be calculated after the signal amplitude matrix S is obtained.

[0109] The following illustrates the above four steps by taking the process of obtaining the envelope value of a texture image (i.e., an example of an evaluation image) as an example.

[0110] According to the first step, the test strip is photographed by the evaluation image acquisition module to obtain an evaluation image A, which has 4 rows and 4 columns (as shown in Table 1), and the pixel values of each pixel point on the evaluation image A are as shown in Table 1. In Table 1, a small square represents a pixel point, and the value in the small square represents the pixel value of the corresponding pixel point. The pixel value corresponding to the pixel point with coordinates (1, 1) is 1, the pixel value corresponding to the pixel point with coordinates (1, 2) is 3, the pixel value corresponding to the pixel point with coordinates (1, 3) is 4, and so on. The pixel values of each pixel point can be determined in this way.

[0111] Table 1

[0112] 1 3 4 5 5 8 3 2 4 4 0 1 2 1 2 3

[0113] According to the second step, the values of the direct current components of each pixel point are calculated by the mean filtering algorithm (Box Filter) in the range defined by the sliding window corresponding to each pixel point, and the values of the direct current components of all pixel points form a direct current component image D.

[0114] Assuming the sliding window parameter R = 1, the size of the sliding window determined according to the parameter is (2R+1)*(2R+1), that is, the size of the sliding window is 3*3, and then the value of the direct current component of a pixel point is determined according to the pixel values of all pixel points in the sliding window. For example, the pixel value of the pixel point with coordinates (1, 1) in Table 1 is 1, and the sliding window corresponding to the pixel point further includes the pixel point with coordinates (2, 1) and a pixel value of 5, the pixel point with coordinates (2, 1) and a pixel value of 3, and the pixel point with coordinates (2, 2) and a pixel value of 8; the pixel value of the pixel point with coordinates (1, 2) is 3, and the sliding window corresponding to the pixel point further includes the pixel point with coordinates (1, 3) and a pixel value of 4, the pixel point with coordinates (2, 2) and a pixel value of 8, and the pixel point with coordinates (2, 3) and a pixel value of 3, and so on. The sum of all pixel values in the sliding window of each pixel point can be determined in this way, and the mean of the sum is solved to obtain the value of the direct current component of the corresponding pixel point, and the value matrix of the direct current component in Table 2 (the table is a direct current image D) is obtained as follows.

[0115] It can be understood that each small square in Table 2 also respectively represents a pixel point, and the data in the square represents the value of the direct current component of the corresponding pixel point.

[0116] According to the set sliding window determination, the value of the direct current component of the pixel point with coordinates (1, 1) is (1+3+5+8) / 4 = 4.25, and the number of pixels in Table 2 is the same as that in Table 1.

[0117] Table 2

[0118] 4.25 4 4.1667 3.5 4.1667 3.5556 3.3333 2.5 4 3.2222 2.6667 1.8333 2.75 2.1667 1.8333 1.5

[0119] According to the above third step, the first image A' after removing the direct current is obtained according to the direct current image D and the image A, and the first image A' is represented by Table 3.

[0120] According to the direct current matrix in Table 2, the first image A' after removing the direct current of the image A is obtained as shown in Table 3, which corresponds to the above third step. Each small square in Table 3 also respectively represents a pixel point, and the data in the square represents the value of the pixel point after removing the direct current. For example, the pixel value of the pixel point with coordinates (1, 1) after removing the direct current is 1-4.25 = -3.25, that is, the value of the pixel point after removing the direct current is obtained by subtracting Table 1 from Table 2 of the same pixel point, and the pixel value in Table 3 is positive and negative.

[0121] Table 3

[0122] -3.25 -1 -0.167 1.5 0.8333 4.4444 -0.333 -0.5 0 0.7778 -2.667 -0.833 -0.75 -1.167 0.1667 1.5

[0123] The envelope values of each pixel point after removing direct current according to the calculation formula of the fourth step are shown in Table 4, and the envelope matrix corresponding to the signal amplitude, that is, the image S is obtained:

[0124] Table 4

[0125] 3.25 3.25 1 1.5 4.4444 4.4444 2.6667 2.6667 0 4.4444 2.6667 2.6667 1.1667 2.6667 1.5 1.5

[0126] It should be noted that in the above examples, the image is represented by a table, that is, in the above examples, the image is represented by a table instead of the traditional matrix representation.

[0127] In the following, the evaluation image obtained by averaging the same pixel points of multiple images is taken as an example to exemplarily describe the process of obtaining the noise ratio according to the signal amplitude, that is, the envelope value, according to some embodiments of the present application.

[0128] L frames of images (L is an integer greater than 1) are continuously collected with a fixed exposure time, and the L frames of images are denoted as: A 1 ,A 2 ,…,A L Wherein, any one frame of image in the L frames of images is represented by the following matrix:

[0129]

[0130] Let the average image of the L frames of images be A (that is, the evaluation image), which is represented by the following matrix, wherein the pixel value of any one pixel point in the image A is the average of the L pixel values of the pixel point on the L frames of images:

[0131]

[0132] First step, calculate the noise amplitude

[0133] Scheme one: calculate the standard deviation of each pixel point in L frames, and take it as the noise amplitude of the coordinate:

[0134]

[0135] Wherein, the physical meaning of the parameter at each coordinate in the matrix is the noise intensity, and the calculation formula after the matrix is the calculation formula of the noise intensity at each coordinate.

[0136] It should be noted that some embodiments of the present application can also use the root mean square error to estimate the noise amplitude.

[0137] Scheme two: take any one frame of image, and suppose it is A 1 Take the root mean square error (RMSE) between it and the average image A as the noise amplitude of the whole image:

[0138]

[0139] Note that the scheme two actually corresponds to the same noise amplitude for each pixel coordinate, and actually only needs to be calculated once. Here it is written in the form of a matrix to make the results of the two schemes consistent, and to simplify the subsequent steps.

[0140] Second step, calculate the signal amplitude

[0141] From any one of the frames of images A 1 ,A 2 ,…,A L , or use the average image A, into the signal amplitude algorithm in the above scheme, to calculate the signal amplitude

[0142] Third step, calculate the signal-to-noise ratio

[0143] Finally, the ratio of N to S is used to calculate the signal-to-noise ratio of the whole image or a set region in the image:

[0144]

[0145] Where i and j are the coordinate values of each pixel point in the whole image or the set region.

[0146] In some embodiments of the present application, the performance of the image acquisition model can be evaluated based on the obtained signal-to-noise ratio.

[0147] Please refer to Figure 7 , Figure 7 The device for evaluating the performance of the image acquisition module provided by the embodiments of the present application is shown, and it should be understood that the device corresponds to the above-mentioned Figure 2 method embodiments, and can perform each step involved in the above-mentioned method embodiments. The specific functions of the device can be referred to the description in the above, and to avoid repetition, the detailed description is appropriately omitted here. The device includes at least one software function module stored in the form of software or firmware in the memory or solidified in the operating system of the device. The device for evaluating the performance of the image acquisition module includes: an evaluation image acquisition module 111 configured to acquire an evaluation image, wherein the evaluation image is an image obtained by using an image acquisition module to image a test pattern; a direct current component removal module 112 configured to remove a direct current component included in the evaluation image to obtain a first image; a signal amplitude acquisition module 113 configured to acquire a signal amplitude of at least part of the pixel points on the first image; and a signal-to-noise ratio acquisition module 114 configured to calculate the signal-to-noise ratio of the image acquisition module to be evaluated according to the signal amplitude and a signal-to-noise ratio calculation formula.

[0148] In some embodiments of the present application, Figure 7The device further includes a noise amplitude acquisition module 115 configured to acquire noise amplitudes of each pixel point using multiple image frames.

[0149] In some embodiments of the present application, Figure 7 The device further includes a quality evaluation module 116 configured to determine whether the corresponding image acquisition module to be evaluated meets the quality requirement according to the signal ratio.

[0150] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the device described above can refer to the corresponding process in the foregoing method, and will not be described in more detail here.

[0151] Some embodiments of the present application provide a readable storage medium having a program stored thereon, and the program can implement the method as Figure 2 described when executed by a processor.

[0152] As Figure 8 shown, some embodiments of the present application provide an electronic device 500 including a memory 510, a processor 520, and a computer program stored in the memory 510 and executable on the processor 520, wherein the processor 520 reads the program from the memory 510 through a bus 530 and implements each embodiment of the method as Figure 2 shown when executing the program.

[0153] The processor 520 can process digital signals and can include various computing structures, such as a complex instruction set computer structure, a reduced instruction set computer structure, or a structure implementing a combination of multiple instruction sets. In some examples, the processor 520 can be a microprocessor.

[0154] The memory 510 can be used to store instructions executed by the processor 520 or data related to the execution process of the instructions. These instructions and / or data can include code for implementing some or all functions of one or more modules described in the embodiments of the present application. The processor 520 of the embodiments of the present disclosure can be used to execute the instructions in the memory 510 to implement the method as shown in Figure 2 . The memory 510 includes a dynamic random access memory, a static random access memory, a flash memory, an optical memory, or other memories well known to those skilled in the art.

[0155] In several embodiments provided in the present application, it should be understood that the disclosed apparatus and method can also be implemented by other means. The apparatus embodiments described above are only illustrative, for example, the flowcharts and block diagrams in the drawings show the possible implementation architecture, function and operation of the apparatus, method and computer program product according to the embodiments of the present application. In this regard, each block in the flowchart or block diagram can represent a module, a program segment or a part of code, which contains one or more executable instructions for implementing the specified logic function. It should also be noted that in some alternative implementation manners, the functions noted in the blocks can also occur in different order from that noted in the drawings. For example, two consecutive blocks can actually be executed substantially in parallel, and sometimes they can also be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagram and / or flowchart, and the combination of blocks in the block diagram and / or flowchart, can be implemented by a dedicated hardware-based system for implementing the specified function or action, or can be implemented by a combination of dedicated hardware and computer instructions.

[0156] In addition, the function modules in the embodiments of the present application can be integrated together to form an independent part, or each module can exist independently, or two or more modules can be integrated to form an independent part.

[0157] If the functions are implemented in the form of software function modules and sold or used as independent products, they can be stored in a computer readable storage medium. Based on this understanding, the technical solutions of the present application can be embodied in the form of a software product in essence or in the form of a part or the whole of the technical solutions that make contributions to the prior art. The computer software product is stored in a storage medium and includes a number of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the embodiments of the present application. The aforementioned storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a magnetic disk or an optical disk, and various media that can store program codes.

[0158] The above merely provides an example of the present application, and is not intended to limit the protection scope of the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application. It should be noted that similar reference numerals and letters represent similar items in the following drawings, and thus, once an item is defined in one drawing, it need not be further defined and explained in subsequent drawings.

[0159] The above merely provides an example of the present application, and is not intended to limit the protection scope of the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application. It should be noted that similar reference numerals and letters represent similar items in the following drawings, and thus, once an item is defined in one drawing, it need not be further defined and explained in subsequent drawings.

[0160] It should be noted that the relational terms herein such as first and second and the like are used solely to distinguish one from another entity or action without necessarily requiring or implying any actual relationship or order between such entities or actions. Moreover, the terms "comprises", "comprising", or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but can also include other elements not expressly listed or inherent to such process, method, article, or apparatus. An element proceeded by "comprises... a" does not, without more constraints, exclude the existence of additional identical elements in the process, method, article, or apparatus that comprises the element.

Claims

1. A method of evaluating performance of an image acquisition module, characterized by, The method comprises: acquiring an evaluation image, wherein the evaluation image is obtained by image acquisition of a test pattern by an image acquisition module; removing a direct current component included in the evaluation image to obtain a first image; acquiring signal amplitudes of at least some pixel points on the first image; calculating a signal-to-noise ratio of the image acquisition module according to the signal amplitudes; the removing of the direct current component included in the evaluation image to obtain the first image comprises: acquiring values of direct current components of each pixel point on the evaluation image; for each pixel point on the evaluation image, obtaining the first image by subtracting the value of the corresponding direct current component from the pixel value; the acquiring of the values of the direct current components of each pixel point on the evaluation image comprises: performing mean filtering on a plurality of pixel values in a sliding window corresponding to any pixel point on the evaluation image to obtain the value of the direct current component of the any pixel point; the signal amplitudes are represented by envelope values; the acquiring of the signal amplitudes of at least some pixel points on the first image comprises: determining envelope values of each pixel point in the at least some pixel points according to positive and negative characteristics of pixel values of the at least some pixel points on the first image; the determining of the envelope values of each pixel point in the at least some pixel points according to the positive and negative characteristics of the pixel values of the at least some pixel points on the first image comprises: if a pixel value of a first pixel point in the at least some pixel points is positive, taking an absolute value of a maximum pixel value in a neighboring region of the first pixel point on the first image as an envelope value of the first pixel point; if a pixel value of a second pixel point in the at least some pixel points is negative, taking an absolute value of a minimum pixel value in a neighboring region of the second pixel point on the first image as an envelope value of the any pixel point; or, if a value of a third pixel point in the at least some pixel points is zero, the envelope value of the third pixel point is zero; wherein the neighboring region is a region defined by a sliding window.

2. The method of claim 1, wherein, The test pattern comprises a stripe pattern or a chessboard pattern, wherein the evaluation image is one image obtained by image acquisition of the test pattern, or the evaluation image is an average image obtained by averaging pixel values of the same pixel points on a plurality of images, and the plurality of images are a plurality of frames of images obtained by multiple image acquisitions of the test pattern by the image acquisition module.

3. The method of any one of claims 1-2, wherein: the evaluation image is obtained by image acquisition of a film having the test pattern illuminated by a light source to be tested by the image acquisition module; the evaluation image is obtained by image acquisition of a rubber test head having the test pattern on a side close to a first display screen by the image acquisition module, wherein the rubber test head is spaced apart from the first display screen; or the evaluation image is obtained by image acquisition of the test pattern displayed by a second display screen by an image acquisition module to be evaluated.

4. The method of claim 2, wherein, Before the calculating the signal-to-noise ratio of the image acquisition module according to the signal amplitude, the method further comprises: acquiring the noise amplitude of each pixel point in the at least partial pixel points; wherein, The calculating the signal-to-noise ratio according to the signal amplitude comprises: calculating the signal-to-noise ratio according to the signal amplitude and a signal-to-noise ratio calculation formula, wherein the signal-to-noise ratio calculation formula is related to the signal amplitude and the noise amplitude of each pixel point in the at least partial pixel points.

5. The method of claim 4, wherein, The acquiring the noise amplitude of each pixel point in the at least partial pixel points comprises: acquiring the noise amplitude through multiple images, wherein the multiple images are obtained by using the image acquisition module to acquire the test pattern multiple times.

6. The method of claim 5, wherein, The number of the multiple images is L, L is an integer greater than 1, wherein, The acquiring the noise amplitude through multiple images comprises: obtaining the noise amplitude by calculating the standard deviation of the changes of each pixel point in L frames.

7. The method of claim 5, wherein, The number of the multiple images is L, L is an integer greater than 1, wherein, The acquiring the noise amplitude through multiple images comprises: taking the root mean square error between any frame of image in L frames and the evaluation image as the noise amplitude of each pixel point, wherein the evaluation image is an image obtained by averaging the pixel values of the same pixel points in the L frames of images.

8. The method of any one of claims 1-2, wherein, The signal-to-noise ratio is calculated by the following formula: wherein i and j are coordinates of the pixel point in a target region, the target region being a region defined by the at least part of the pixel points, representing a signal amplitude corresponding to the pixel point with coordinates i and j, representing a noise amplitude corresponding to the pixel point with coordinates i and j.

9. The method of any one of claims 1-2, wherein, After the calculating the signal-to-noise ratio of the image acquisition module according to the signal amplitude, the method further comprises: evaluating the performance of the image acquisition module according to the signal-to-noise ratio.

10. The method of any one of claims 1-2, wherein, The signal-to-noise ratio of the image acquisition module to be evaluated is represented by the at least partial pixel points.

11. An apparatus for evaluating the performance of an image acquisition module, characterized in that, The device comprises: an evaluation image acquisition module configured to acquire an evaluation image, wherein the evaluation image is obtained by using an image acquisition module to acquire a test pattern; a direct current component removal module configured to remove the direct current component included in the evaluation image to obtain a first image; a signal amplitude acquisition module configured to acquire the signal amplitude of at least partial pixel points on the first image; a signal-to-noise ratio acquisition module configured to calculate the signal-to-noise ratio of the image acquisition module to be evaluated according to the signal amplitude; the direct current component removal module is configured to acquire the value of the direct current component of each pixel point on the evaluation image; for each pixel point on the evaluation image, the pixel value is subtracted by the value of the corresponding direct current component to obtain the first image; the direct current component removal module is configured to perform mean filtering on multiple pixel values of any pixel point in a sliding window corresponding to the pixel point on the evaluation image to obtain the value of the direct current component of the pixel point; the signal amplitude is represented by an envelope value; the signal amplitude acquisition module is specifically configured to determine the envelope value of each pixel point in the at least partial pixel points according to the positive and negative characteristics of the pixel values of the at least partial pixel points on the first image; The determination of the envelope value of each pixel point in the at least partial pixel points according to the positive and negative characteristics of the pixel value of the at least partial pixel points on the first image comprises: if the sign of the pixel value of a first pixel point in the at least partial pixel points is positive, taking the absolute value of the maximum pixel value in the adjacent region of the first pixel point on the first image as the envelope value of the first pixel point; if the sign of the pixel value of a second pixel point in the at least partial pixel points is negative, taking the absolute value of the minimum pixel value in the adjacent region of the second pixel point on the first image as the envelope value of the second pixel point; or if the value of a third pixel point in the at least partial pixel points is zero, the envelope value of the third pixel point is zero; wherein the adjacent region is a region defined by a sliding window.

12. A readable storage medium, having a program stored thereon, characterized in that, The program, when executed by a processor, can implement the method of any one of claims 1-10.

13. An electronic device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein, The processor, when executing the program, can implement the method of any one of claims 1-10.

Images