Pixel saturation state detection method, identification method, device, equipment and medium

Abstract

The application relates to a method for detecting a pixel saturation state, a method for identifying performance decay of a detector, a device for detecting a pixel saturation state, electronic equipment, a storage medium and a computer program product. The method comprises the following steps: when frame transfer is performed on an acquired image that produces a tailing effect, determining a first gray value of the acquired image based on a preset dark pixel region; the dark pixel region is a region where a plurality of blocked pixels arranged in an image imaging area corresponding to the acquired image are located; then, after the frame transfer, determining a second gray value of the acquired image based on accumulated photoelectric charge of each pixel in the acquired image; finally, determining a pixel saturation state of the acquired image based on the first gray value and the second gray value. The method can detect the saturation state of the pixel from multiple angles, thereby improving the convenience and accuracy of the pixel saturation state detection.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of computer, in particular to a pixel saturation state detection method, a detector performance decay identification method, a pixel saturation state detection device, an electronic device, a storage medium and a computer program product. BACKGROUND

[0002] With the rapid development of aerospace technology, large-area frame type CCD cameras become the main development direction of aerospace cameras due to their high resolution and large field of view. Among several face array CCD structures, the interline transfer face array CCD has the characteristics of fast transfer rate and electronic shutter function, and is particularly suitable for calculating whether the pixels in the image collected by the CCD camera reach the saturation state.

[0003] In the prior art, the saturation state of the collected image is calculated by setting a test device to test the CCD camera under at least 10 different exposure amounts, calculating the average saturation value of each group of collected images, and determining the saturation state of the collected image according to the size between the inherent determination threshold of the CCD camera and the average saturation value of the collected image.

[0004] However, the performance of the CCD camera may age and decline, and in space applications, charged particles and vacuum environments in space may also cause changes in the performance of the CCD camera. These two factors may cause changes in the inherent determination threshold of the CCD camera. If the original inherent determination threshold is still used to determine the saturation state of the collected image, deviation may occur. SUMMARY

[0005] The present disclosure provides a pixel saturation state detection method, a detector performance decay identification method, a pixel saturation state detection device, an electronic device, a storage medium and a computer program product to at least solve the problem of inaccurate determination of the saturation state of the image in the related art. The technical solutions of the present disclosure are as follows:

[0006] According to a first aspect of the embodiments of the present disclosure, a pixel saturation state detection method is provided, comprising:

[0007] When frame transfer is performed on the collected image that produces a tailing effect, a first gray value of the collected image is determined based on a preset dark pixel region; the dark pixel region is a region where a plurality of blocked pixels arranged in an image imaging area corresponding to the collected image are located;

[0008] After the frame transfer, a second gray value of the collected image is determined based on the accumulated photoelectric charge amount of each pixel in the collected image;

[0009] determine a first gray value of the acquisition image based on a preset dark pixel region when frame transfer is performed on the acquisition image generating the smear effect.

[0010] In an exemplary embodiment, the first gray value of the acquisition image is determined based on a preset dark pixel region when frame transfer is performed on the acquisition image generating the smear effect, comprising:

[0011] When frame transfer is performed on the acquisition image, the gray value of each dark pixel in the dark pixel region is obtained.

[0012] The first gray value of the acquisition image is determined based on the average gray value of each dark pixel corresponding to each row in the dark pixel region.

[0013] In an exemplary embodiment, the second gray value of the acquisition image is determined based on the accumulated photoelectric charge of each pixel in the acquisition image after the frame transfer, comprising:

[0014] The exposure time of the acquisition image and the frame transfer time of the charge package between adjacent pixels when the frame transfer is performed on the acquisition image are obtained.

[0015] The second gray value of the acquisition image is determined based on the accumulated photoelectric charge, the exposure time and the frame transfer time.

[0016] In an exemplary embodiment, the second gray value of the acquisition image is determined based on the accumulated photoelectric charge, the exposure time and the frame transfer time, comprising:

[0017] The transfer time factor of the frame transfer is determined based on the exposure time and the frame transfer time.

[0018] The second gray value of the acquisition image is determined based on the third gray value of the acquisition image corresponding to the accumulated photoelectric charge and the transfer time factor.

[0019] The second gray value of the acquisition image is used to represent the true gray value of the acquisition image in the case that the acquisition image generates the smear effect; and the third gray value of the acquisition image is used to represent the original gray value of the acquisition image in the case that the acquisition image does not generate the smear effect.

[0020] In an exemplary embodiment, the pixel saturation state of the acquisition image is determined based on the first gray value and the second gray value, comprising:

[0021] The loss gray value accumulated in each pixel of the acquisition image in the case that the smear effect is generated is determined based on the difference between the second gray value and the third gray value.

[0022] determine a saturation state of a pixel of the acquisition image based on a size relationship between the first gray value and the loss gray value.

[0023] In an exemplary embodiment, the determining the saturation state of the pixel of the acquisition image based on the size relationship between the first gray value and the loss gray value includes the following two items:

[0024] in response to the first gray value of the acquisition image being greater than the second gray value of the acquisition image, the saturation state of the pixel of the acquisition image is a saturated state;

[0025] in response to the first gray value of the acquisition image being less than or equal to the second gray value of the acquisition image, the saturation state of the pixel of the acquisition image is an unsaturated state.

[0026] According to a second aspect of the embodiments of the present disclosure, a performance degradation identification method of a detector is provided, including:

[0027] obtaining a performance determination threshold of the detector and first and second gray values of an acquisition image; the performance determination threshold is used to represent a gray value of a pixel of an acquisition image when the performance of the detector is in a critical saturation state in a case where the performance of the detector is not degraded; the first and second gray values of the acquisition image are obtained by using any one of the pixel saturation state detection methods described above;

[0028] in a case where the first gray value of the acquisition image is greater than the second gray value of the acquisition image, if the first gray value is less than the performance determination threshold, it is identified that the performance of the detector is negative degradation; or

[0029] in a case where the first gray value of the acquisition image is greater than the second gray value of the acquisition image, if the first gray value is greater than the performance determination threshold, it is identified that the performance of the detector is positive degradation.

[0030] According to a third aspect of the embodiments of the present disclosure, a pixel saturation state detection method is provided, including:

[0031] a first gray unit configured to determine a first gray value of an acquisition image based on a preset dark pixel region when frame transfer is performed on the acquisition image that produces a tailing effect; the dark pixel region is a region where a plurality of blocked pixels are arranged in an image imaging area corresponding to the acquisition image;

[0032] a second gray unit configured to determine a second gray value of the acquisition image based on a cumulative photocharge amount of each pixel in the acquisition image after the frame transfer;

[0033] The state detection unit is configured to determine a pixel saturation state of the captured image based on the first gray value and the second gray value.

[0034] According to a fourth aspect of embodiments of the present disclosure, an electronic device is provided, comprising:

[0035] a processor;

[0036] a memory for storing executable instructions of the processor;

[0037] The processor is configured to execute the executable instructions to implement the pixel saturation state detection method and / or the performance degradation identification method of the detector according to any one of the above.

[0038] According to a fifth aspect of embodiments of the present disclosure, a computer readable storage medium is provided, the computer readable storage medium comprising program data, when the program data is executed by a processor of a server, the server is enabled to execute the pixel saturation state detection method and / or the performance degradation identification method of the detector according to any one of the above.

[0039] According to a sixth aspect of embodiments of the present disclosure, a computer program product is provided, the computer program product comprising program instructions, when the program instructions are executed by a processor of a server, the server is enabled to execute the pixel saturation state detection method and / or the performance degradation identification method of the detector according to any one of the above.

[0040] The technical solutions provided by the embodiments of the present disclosure at least bring the following beneficial effects:

[0041] The method first determines a first gray value of the acquisition image based on a preset dark pixel region when frame transfer is performed on the acquisition image that produces a tailing effect, wherein the dark pixel region is a region where a plurality of blocked pixels are arranged in an image imaging area corresponding to the acquisition image; then, determines a second gray value of the acquisition image based on the accumulated photoelectric charge of each pixel in the acquisition image after frame transfer; and finally, determines the saturation state of the pixels in the acquisition image based on the first gray value and the second gray value. In this way, on the one hand, the saturation state of the pixels in the acquisition image is detected by comprehensively using the first gray value obtained from the dark pixel region of the acquisition image and the second gray value obtained from the accumulated photoelectric charge of each pixel, so as to detect the saturation state of the pixels from multiple angles, thereby improving the convenience and universality of the saturation state detection of the pixels; on the other hand, unlike the saturation state detection of the pixels in the prior art by using the inherent determination threshold of the detection device, the saturation state of the pixels is detected by using the gray value obtained from the dark pixel region and the gray value corresponding to the accumulated photoelectric charge of the pixels, so as to avoid the change of the inherent determination threshold of the detection device caused by decay, damage and the like, thereby improving the accuracy and reliability of the saturation state detection of the pixels, and further ensuring the accuracy and reliability of the transformer corresponding to the power system.

[0042] It should be understood that the foregoing general description and the following detailed description are only exemplary and explanatory, and cannot limit the present disclosure. BRIEF DESCRIPTION OF DRAWINGS

[0043] The accompanying drawings incorporated in the specification hereof and forming a part thereof illustrate embodiments consistent with the present disclosure and together with the description are used to explain the principles of the present disclosure, and are not intended to limit the present disclosure.

[0044] Figure 1 is an application environment diagram of a pixel saturation state detection method according to an exemplary embodiment.

[0045] Figure 2 is a flowchart of a pixel saturation state detection method according to an exemplary embodiment.

[0046] Figure 3 is a structural schematic diagram of a CCD detector according to an exemplary embodiment.

[0047] Figure 4 is a flowchart of a step of determining a first gray value of an acquisition image according to an exemplary embodiment.

[0048] Figure 5 is a flowchart of a step of determining a second gray value of an acquisition image according to an exemplary embodiment.

[0049] Figure 6is a flowchart of another step of determining a second gray value of an acquired image according to an example embodiment.

[0050] Figure 7 is a flowchart of a step of determining a pixel saturation state of an acquired image according to an example embodiment.

[0051] Figure 8 is a flowchart of a method of identifying performance degradation of a detector according to an example embodiment.

[0052] Figure 9 is a block diagram of a detection device of a pixel saturation state according to an example embodiment.

[0053] Figure 10 is a block diagram of a device of identifying performance degradation of a detector according to an example embodiment.

[0054] Figure 11 is a block diagram of an electronic device for detecting a pixel saturation state according to an example embodiment.

[0055] Figure 12 is a block diagram of a computer readable storage medium for detecting a pixel saturation state according to an example embodiment.

[0056] Figure 13 is a block diagram of a computer program product for detecting a pixel saturation state according to an example embodiment. DETAILED DESCRIPTION

[0057] In order to make the purposes, technical solutions and advantages of the present application clearer, the present application is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and not intended to limit the present application.

[0058] The term "and / or" in the embodiments of the present application means any and all possible combinations of the associated listed items. It should also be noted that when used in the present specification, "comprise / comprising" specifies the presence of stated features, integers, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements and / or components and / or groups thereof.

[0059] The terms "first", "second", etc. in this application are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but can optionally include steps or units not listed, or can optionally include other steps or units inherent to the process, method, product or device.

[0060] In addition, although the terms "first", "second", etc. are used repeatedly in this application to describe various operations (or various elements or various applications or various instructions or various data), etc., these operations (or elements or applications or instructions or data) should not be limited by these terms. These terms are only used to distinguish one operation (or element or application or instruction or data) from another operation (or element or application or instruction or data). For example, the first pixel response gray value can be called the second pixel response gray value, and the second pixel response gray value can also be called the first pixel response gray value, only the range included by the two is different, without departing from the scope of the application, the first pixel response gray value and the second pixel response gray value are both the collection of the influence of the smear effect generated by the acquisition image on the gray value of the pixel, only the two are not the same gray value influence of the pixel.

[0061] The pixel saturation state detection method provided by the embodiments of the application can be applied to the application environment as shown in Figure 1 The terminal 102 communicates with the server 104 through a communication network. The data storage system can store data required to be processed by the server 104. The data storage system can be integrated on the server 104, or can be placed on a cloud or other network server.

[0062] In some embodiments, referring to Figure 1 The server 104 first determines a first gray value of the acquisition image based on a preset dark pixel region when performing frame transfer on the acquisition image generating the smear effect; wherein the dark pixel region is a region where a plurality of blocked pixels are arranged in the image imaging area corresponding to the acquisition image; then the server 104 determines a second gray value of the acquisition image based on the accumulated photoelectric charge of each pixel in the acquisition image after frame transfer; finally, the server 104 determines the pixel saturation state of the acquisition image based on the first gray value and the second gray value.

[0063] In some embodiments, the terminal 102 (e.g., mobile terminal, stationary terminal) can be implemented in various forms. Among others, the terminal 102 can be a mobile terminal including, for example, a mobile phone, a smart phone, a notebook computer, a portable handheld device, a personal digital assistant (PDA), a tablet computer (PAD), etc., which can integrate a first gray scale value obtained from a dark pixel area of a captured image and a second gray scale value obtained from a cumulative photocharge amount of each pixel to perform a saturation state detection of the pixels in the captured image. The terminal 102 can also be an Automated Teller Machine (ATM), a kiosk, a digital TV, a desktop computer, a stationary computer, etc., which can integrate a first gray scale value obtained from a dark pixel area of a captured image and a second gray scale value obtained from a cumulative photocharge amount of each pixel to perform a saturation state detection of the pixels in the captured image.

[0064] Hereinafter, it is assumed that the terminal 102 is a stationary terminal. However, those skilled in the art will appreciate that the configuration according to the embodiments of the present disclosure can also be applied to a mobile type terminal 102 if there are operations or elements specifically for mobile purposes.

[0065] In some embodiments, the data processing component executed by the server 104 can load any of various additional server applications and / or middleware applications, which can include, for example, HTTP (HyperText Transfer Protocol), FTP (File Transfer Protocol), CGI (Common Gateway Interface), RDBMS (Relational Database Management System), etc.

[0066] In some embodiments, the server 104 can be implemented with a single server or a server cluster composed of a plurality of servers. The server 104 can be adapted to execute one or more application services or software components of the terminal 102 described in the foregoing disclosure.

[0067] In some embodiments, the one or more application services or software components provided by the server 104 include a portal in the foreground to provide a one-to-one application service to a user and a plurality of business systems in the background to process data, so as to extend the determination of the first and second gray scale values of the captured image to a device side or a client side, thereby enabling the user to perform a saturation state detection of the pixels in the captured image at any time and in any place.

[0068] In some embodiments, the pixel saturation detection function on the device or client side can be a computer program running in user mode to perform one or more specific tasks. This program can interact with the user and has a visual user interface. The device or client side can include two parts: a graphical user interface (GUI) and an engine, which together provide a digital client system with various application services to the user in the form of a user interface.

[0069] In some embodiments, a user can input corresponding code data or control parameters to the device or client through the input device in the terminal 102 to execute the application services of the computer program in the server 104 and display the application services in the user interface.

[0070] In some embodiments, the operating system running on the device or client may include various versions of Microsoft operating systems. Apple and / or Linux operating system, various commercial or similar Operating systems (including but not limited to various GNU / Linux operating systems, Google) OS and / or mobile operating systems, such as Phone OS OS OS operating systems, as well as other online or offline operating systems, are not specifically limited here.

[0071] In some embodiments, such as Figure 2 As shown, a method for detecting pixel saturation is provided, which can be applied to... Figure 1 Taking server 104 as an example, the method includes the following steps:

[0072] Step S11: When performing frame transfer on the acquired image that produces a trailing effect, the first gray value of the acquired image is determined based on the preset dark pixel region.

[0073] In one embodiment, the acquired image can be obtained by a frame-transfer type CCD detector through acquisition and imaging.

[0074] In some embodiments, such as Figure 3 As shown, Figure 3 This is a schematic diagram of a CCD detector provided in this application. The frame-transfer CCD detector consists of an imaging area A1, an image storage area A2, and a data readout area A3 from top to bottom. The data readout area A3 can be various types of registers used for reading in and out image data acquired and generated by the frame-transfer CCD detector.

[0075] In some embodiments, the frame transfer type CCD detector has a structure feature that the imaging area A1 is separated from the image storage area A2, the imaging area A1 is composed of vertical charge coupled channels arranged in parallel, and the CCD column number and bit number of the imaging area A1 and the image storage area A2 are the same. Each transfer unit of the data readout area A3 corresponds to a vertical column charge coupled channel.

[0076] In some embodiments, when the data integration of the image acquisition by the frame transfer type CCD detector ends, the imaging area A1 and the image storage area A2 are driven at the same speed to transfer the field information of the imaging area A1 to the image storage area A2, the optical signal of the image storage area A2 is transferred to the data readout area A3 row by row to form a gray value through analog-digital conversion (ADC), and at the same time, the imaging area starts another field integration.

[0077] In some embodiments, the process continues as shown in Figure 3 In order to avoid the generated acquisition image from showing tailing due to the generated tailing effect, the frame transfer type CCD detector is provided with a dark pixel area A4 above the imaging area A1. The dark pixel area A4 is composed of multiple dark rows arranged above the imaging area A1.

[0078] In an embodiment, the dark pixel area A4 is a region where multiple blocked pixels are arranged in the image imaging area corresponding to the acquisition image.

[0079] In some embodiments, the dark rows are a plurality of blocked pixels arranged at the top or bottom of the imaging area of the frame transfer type area array CCD.

[0080] In some embodiments, during the frame transfer process, the charge packets of the dark rows pass through the imaging area A1 and additionally generate extra photocharges, and the amount of the extra photocharges is δ times the photocharges generated during the exposure time of the pixels in the same column of the imaging area A1, so that the size of the dark row signal can accurately reflect the size of the tailing photocharges. The method of subtracting the average gray value of the dark row pixels in the same column from the gray value of each pixel of the CCD output image to obtain the true value of the image is called the dark row method. The dark row method is not limited by the pixel matrix and has a wide range of applications.

[0081] In some embodiments, the server obtains the gray value corresponding to the additional tailing photocharges generated in the dark pixel area when performing frame transfer on the acquisition image to determine the first gray value of the acquisition image.

[0082] Step S12, after frame transfer, determining the second gray value of the acquisition image based on the accumulated photocharge amount of each pixel in the acquisition image.

[0083] In one embodiment, the server first determines the sum of the accumulated photoelectric charges of each pixel in the acquired image after the three processes of brush frame, exposure and frame transfer, i.e. the accumulated photoelectric charges, by using the frame transfer area array CCD. Then, the server determines the real gray value of the acquired image in the case that the acquired image produces the smear effect and the original gray value of the acquired image in the case that the acquired image does not produce the smear effect (i.e. determines by using the matrix method) in the case that the acquired image produces the smear effect and the original gray value of the acquired image in the case that the acquired image does not produce the smear effect, by using the photoelectric charge matrix expression. Finally, the server determines the second gray value of the acquired image based on the difference between the real gray value of the acquired image and the original gray value of the acquired image represented by the photoelectric charge matrix expression.

[0084] In step S13, the saturation state of the pixels in the acquired image is determined based on the first gray value and the second gray value.

[0085] In one embodiment, if the server determines that the first gray value of the acquired image is greater than the second gray value of the acquired image (i.e. the first gray value of the acquired image calculated by the dark row method is greater than the second gray value of the acquired image calculated by the matrix method), the server determines that the saturation state of the pixels in the acquired image is the saturated state.

[0086] In another embodiment, if the server determines that the first gray value of the acquired image is less than or equal to the second gray value of the acquired image (i.e. the first gray value of the acquired image calculated by the dark row method is less than or equal to the second gray value of the acquired image calculated by the matrix method), the saturation state of the pixels in the acquired image is the unsaturated state.

[0087] In the detection process of the above-mentioned pixel saturation state, the server first determines a first gray value of the acquisition image based on a preset dark pixel region when frame transfer is performed on the acquisition image that produces the tailing effect; the dark pixel region is a region where a plurality of blocked pixels arranged in an image imaging area corresponding to the acquisition image are located; then, a second gray value of the acquisition image is determined based on the accumulated photoelectric charge of each pixel in the acquisition image after frame transfer; finally, the pixel saturation state of the acquisition image is determined based on the first gray value and the second gray value. In this way, on the one hand, the first gray value obtained from the dark pixel region of the acquisition image and the second gray value obtained from the accumulated photoelectric charge of each pixel are combined to detect the saturation state of the pixels in the acquisition image, which can detect the saturation state of the pixels from multiple angles, thereby improving the convenience and universality of the pixel saturation state detection; on the other hand, unlike the prior art that detects the saturation state of the pixels by using the inherent determination threshold of the detection device, the present case detects the saturation state of the pixels by using the gray value obtained from the dark pixel region and the gray value corresponding to the accumulated photoelectric charge of the pixels, which can avoid changes in the inherent determination threshold of the detection device caused by decay, damage and the like, thereby improving the accuracy and reliability of the pixel saturation state detection, and further ensuring the accuracy and reliability of the transformer corresponding to the power system.

[0088] As can be understood by those skilled in the art, in the above-mentioned method of the specific implementation, the disclosed method can be implemented in a more specific manner. For example, the above-mentioned implementation of determining the first gray value of the acquisition image based on the preset dark pixel region is only illustrative.

[0089] For example, the way in which the server determines the first gray value of the acquisition image, or the way in which the second gray value of the acquisition image is determined, and the like, is only one set of ways, and other division ways can be used in actual implementation, for example, the first gray value and the second gray value can be combined or integrated into another system, or some features can be ignored or not executed.

[0090] In an exemplary embodiment, referring to Figure 4 , Figure 4 is a flowchart of an embodiment of determining the first gray value of the acquisition image in the present application. In step S11, the server determines the first gray value of the acquisition image based on the preset dark pixel region when frame transfer is performed on the acquisition image that produces the tailing effect, which can be implemented by the following way:

[0091] In step S111, the gray value of each dark pixel in the dark pixel region is obtained when the acquisition image is frame transferred.

[0092] In some embodiments, the dark pixel region is not illuminated when the CCD is exposed, and the signal of each dark pixel in the dark pixel region is completely absent when the CCD is exposed, while each dark pixel in the dark pixel region generates a signal when the charge transfer output passes through the imaging region exposure, and the signal size of each dark pixel in the dark pixel region can reflect the size of the additional signal corresponding to the smear effect, so that the first gray value of the acquisition image when the server performs frame transfer on the acquisition image can be calculated. Therefore, the server first obtains the gray value of each dark pixel in the dark pixel region when frame transfer is performed. The server can obtain the gray value of each dark pixel in the dark pixel region when frame transfer is performed by the following formula:

[0093]

[0094] In the formula, only the row direction (x) of the acquisition image is averaged, which is mainly based on the principle of the smear effect. DN 暗行 represents the gray average value of each dark row in the dark pixel region, DN(x, y) represents the image gray value of the coordinates x and y, and N is the number of dark rows. y is the column that needs to be judged whether there is a saturated pixel.

[0095] Step S112, determining the first gray value of the acquisition image based on the gray average value of each dark pixel corresponding to each row in the dark pixel region.

[0096] In an embodiment, if there are multiple dark rows (i.e., N>1) in the dark pixel region, the average result of each dark row is obtained as the first gray value of the acquisition image.

[0097] In an embodiment, referring to Figure 5 , Figure 5 is a flowchart of an embodiment for determining the second gray value of the acquisition image in the present application. In step S12, the server determines the second gray value of the acquisition image based on the accumulated charge amount of each pixel in the acquisition image after the frame transfer, and the process can be realized by the following way:

[0098] Step S121, obtaining the exposure time of the acquisition image, and the frame transfer time of the charge packet between adjacent pixels when the acquisition image is frame transferred.

[0099] In an embodiment, the imaging process of the frame transfer area CCD on the acquisition image can include:

[0100] Step 1, charge clearing of the photosensitive region (i.e., frame brushing process). At the end of the frame brushing, the photocharge appears as a smear from the target projection position to the bottom of the CCD.

[0101] The charge clearing process can be regarded as the movement of empty charge packets from the top of the CCD array (ROW1) to the bottom (ROW512). The transfer of charge packets between the pixels is not instantaneous, and in the absence of mechanical or electronic shutter, the imaging area is always in light, and each pixel continuously generates new photo charges during the transfer of charge packets.

[0102] The photo charges generated during the charge clearing process for the nth column of pixels can be represented by a matrix as follows:

[0103]

[0104] In the formula, Y'm is the charge amount of the mth row, and Ym is the photo charge generated by the mth row of pixels per unit time.

[0105] Step 2, exposure imaging. During the exposure time, all the pixels in the imaging area of the CCD will convert the received photons into photo charges, and a frame of image will be recorded in the form of charge signals. At the end of the exposure, for the nth column of pixels, the photo charges accumulated during the exposure time can be represented by a matrix as follows:

[0106]

[0107] In the formula, Y"m is the photo charge of the mth row, and T is the exposure time.

[0108] Step S122, based on the accumulated photo charge amount, the exposure time and the frame transfer time, determine the second gray value of the collected image.

[0109] In an exemplary embodiment, referring to Figure 6 , Figure 6 is a flowchart of another embodiment of the present application for determining the second gray value of the collected image. In step S122, the server determines the second gray value of the collected image based on the accumulated photo charge amount, the exposure time and the frame transfer time. The process can be implemented in the following way:

[0110] Step S1221, based on the exposure time and the frame transfer time, determine the transfer time factor of the frame transfer.

[0111] In an embodiment, the imaging process of the frame transfer area CCD on the collected image can further include:

[0112] Step 3, frame transfer. After the imaging of the image is completed, the image is transferred from the imaging area to the storage area in the form of charge signals to wait for readout. When the charge packet above the target projection position "passes" the projection position, additional photocharges are generated. At the end of the frame transfer, these photocharges appear as smearing from the target projection position to the top of the CCD. For the nth column of pixels, the photocharges generated during the transfer of the imaging area to the storage area can be represented by the matrix:

[0113]

[0114] where Ym'" is the photocharge of the mth row.

[0115] Step 4, readout of pixel charges. After the frame transfer is completed, the charges in the storage area are read out in turn by the readout register row by row, and the amount of charge of each pixel is converted into a voltage signal. The storage area is covered with light shielding material, so it is not affected by light during the readout. The readout photocharges include the sum of the charges accumulated during the three processes of brush frame, exposure, and frame transfer. Therefore, for the nth column of pixels, the matrix expression of the readout photocharges is:

[0116]

[0117] where Xm is the photocharge of the mth row.

[0118] In an embodiment, δ is used to represent the transfer time factor of the frame transfer, i.e., the row movement time factor of the photocharge. Wherein, the server determines the transfer time factor of the frame transfer as δ = t / T based on the exposure time T and the frame transfer time t.

[0119] Step S1222, determining the second gray value of the acquisition image based on the third gray value of the acquisition image corresponding to the accumulated photocharge amount and the transfer time factor.

[0120] In an embodiment, the server determines the third gray value of the acquisition image corresponding to the accumulated photocharge amount based on the transfer time factor δ of the frame transfer and the matrix expression of the readout photocharge of the pixel charge. Wherein, the third gray value of the acquisition image corresponding to the accumulated photocharge amount can be obtained by the following matrix expression:

[0121]

[0122] The above formula is converted as follows:

[0123]

[0124] where Y"m is the photocharge accumulated in the mth row within the exposure time T, i.e., the true gray value of the acquisition image in the case of smearing effect of the acquisition image. Xm is the photocharge of the mth row, i.e., the original gray value of the acquisition image in the case of no smearing effect of the acquisition image.

[0125] During the imaging process, the total amount of photocharge collected by a pixel is the sum of the photocharge generated during the exposure time of that pixel and δ times the photocharge generated during the exposure time of the pixels in the same photosensitive area. δ times the photocharge generated during the exposure time of the pixels in the same photosensitive area is the amount of charge in the trailing phase.

[0126] In one embodiment, the second grayscale value of the acquired image is used to characterize the true grayscale value of the acquired image when the acquired image produces a trailing effect; the third grayscale value of the acquired image is used to characterize the original grayscale value of the acquired image when the acquired image does not produce a trailing effect.

[0127] In one exemplary embodiment, see Figure 7 , Figure 7 This is a schematic flowchart illustrating an embodiment of determining the pixel saturation state of an acquired image in this application. In step S13, the process by which the server determines the pixel saturation state of the acquired image based on the first grayscale value and the second grayscale value can be implemented in the following manner:

[0128] Step S131: Based on the difference between the second gray value and the third gray value, determine the accumulated loss gray value of each pixel in the acquired image when a trailing effect occurs.

[0129] In one embodiment, the grayscale value generated by the trailing effect is the difference between the second grayscale value and the third grayscale value, that is, the accumulated grayscale value of a certain pixel in the acquired image when the trailing effect occurs. The accumulated grayscale value of a certain pixel in the acquired image can be calculated using the following formula:

[0130]

[0131] DN in the formula m This represents the grayscale value produced by the trailing effect of a single pixel in the m-th row.

[0132] Furthermore, the server will store all DNs m The values ​​are summed to obtain the total gray value caused by the trailing effect, which is the accumulated gray value loss of all pixels in the image when the trailing effect occurs. The calculation formula is as follows:

[0133]

[0134] Step S132: Based on the relationship between the first gray value and the lost gray value, determine the pixel saturation state of the acquired image.

[0135] In one embodiment, if the server responds to the first gray value of the acquired image being greater than the second gray value of the acquired image (i.e., the first gray value of the acquired image calculated by the server using the dark method is greater than the second gray value of the acquired image calculated by the server using the matrix method), then the server determines that the pixel saturation state of the acquired image is saturated.

[0136] In another embodiment, if the server responds to the first gray value of the acquired image being less than or equal to the second gray value of the acquired image (i.e., the first gray value of the acquired image calculated by the server using the dark method is less than or equal to the second gray value of the acquired image calculated by the server using the matrix method), the pixel saturation state of the acquired image is an unsaturated state.

[0137] In some embodiments, such as Figure 8 As shown, a method for identifying the performance degradation of a detector is provided, which can be applied to... Figure 1 Taking server 104 as an example, the method includes the following steps:

[0138] Step S21: Obtain the detector's performance judgment threshold and the first grayscale value and second grayscale value of the acquired image.

[0139] In one embodiment, the first grayscale value and the second grayscale value of the acquired image obtained by the server are obtained using the pixel saturation detection method in the above embodiment.

[0140] In one embodiment, the performance determination threshold is used to characterize the performance of the detector and identify the grayscale value of a pixel in the acquired image at critical saturation without degradation.

[0141] In one embodiment, the detector is an optical remote sensing detector of a frame-shifting area array CCD, which is used to detect the pixel saturation level in the acquired image. Specifically, when the light signal received by the detector from the acquired image and the output gray value no longer satisfy the linear relationship (i.e., when the light energy increases, the gray value no longer increases proportionally), the pixels in the acquired image reach a saturated state.

[0142] In some embodiments, the detector has a preset saturation threshold for grayscale values. Under normal detector conditions, when the detector detects that the grayscale value of the acquired image is less than the saturation threshold, the pixels in the acquired image are not saturated; when the detector detects that the grayscale value of the acquired image is equal to the saturation threshold, the pixels in the acquired image are saturated.

[0143] In some embodiments, when the performance of the detector appears to be aging and the performance is declining (e.g., in space applications, the environment of charged particles and vacuum in space also causes the performance of the detector to change), the detector calculates the change in the gray value of the acquired image, and if the previous saturated gray value data is still used to determine the pixel saturation state, deviation will occur.

[0144] Step S22, in the case that the first gray value of the acquired image is greater than the second gray value of the acquired image, if the first gray value is less than the performance determination threshold, the performance of the detector is identified as negative decay.

[0145] As an example, the saturation threshold preset by the detector is 4000, the first gray value of the acquired image determined by the server is 3950, and the second gray value of the acquired image is 3900. Based on the pixel saturation state detection method in the above embodiments, it can be known that the pixels in the acquired image have reached the saturation state at this time, and the saturated gray value is 3950. Since the saturation threshold preset by the detector is greater than the first gray value of the acquired image in the saturated state at this time, the server identifies the performance of the detector as negative decay (i.e., the pixels in the acquired image have already saturated when the gray value of the acquired image has not reached the saturation threshold preset by the detector).

[0146] Step S23, in the case that the first gray value of the acquired image is greater than the second gray value of the acquired image, if the first gray value is greater than the performance determination threshold, the performance of the detector is identified as positive decay.

[0147] As an example, the saturation threshold preset by the detector is 4000, the first gray value of the acquired image determined by the server is 4200, and the second gray value of the acquired image is 4100. Based on the pixel saturation state detection method in the above embodiments, it can be known that the pixels in the acquired image have reached the saturation state at this time, and the saturated gray value is 4200. Since the saturation threshold preset by the detector is less than the first gray value of the acquired image in the saturated state at this time, the server identifies the performance of the detector as positive decay (i.e., the pixels in the acquired image have not yet saturated when the gray value of the acquired image has already reached the saturation threshold preset by the detector).

[0148] The above scheme, on the one hand, comprehensively detects the saturation state of the pixels in the collected image by combining the first gray value obtained from the dark pixel area and the second gray value obtained from the accumulated photoelectric charge of each pixel, which can detect the saturation state of the pixels from multiple angles, thereby improving the convenience and universality of the pixel saturation state detection; on the other hand, unlike the prior art which detects the saturation state of the pixels by the inherent determination threshold of the detection device, the present case detects the saturation state of the pixels by using the gray value obtained from the dark pixel area and the corresponding gray value of the accumulated photoelectric charge of the pixels, which can avoid the change of the inherent determination threshold of the detection device due to decay, damage and other reasons, thereby improving the accuracy and reliability of the pixel saturation state detection, and further ensuring the accuracy and reliability of the transformer corresponding to the power system.

[0149] It should be understood that, although Figures 2-8 The steps in the flowchart of the method are displayed in sequence according to the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified herein, the execution of these steps is not strictly limited in sequence, and these steps can be executed in other orders. Moreover, Figures 2-8 At least part of the steps in the method can include multiple steps or multiple stages, which are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily sequential, but can be executed alternately or alternately with at least part of other steps or steps or stages in other steps.

[0150] It can be understood that the same / similar parts between each embodiment of the above method in the specification can be mutually referred to, and each embodiment focuses on the differences from other embodiments, and the related parts can be referred to the description of other method embodiments.

[0151] Figure 9 is a pixel saturation state detection device block diagram provided by an embodiment of the present application. Referring to Figure 9 The pixel saturation state detection device 10 includes a first gray unit 11, a second gray unit 12, and a state detection unit 13.

[0152] The first gray unit 11 is configured to acquire a plurality of index data of a target oil paper; the plurality of index data are used to represent the insulation degradation degree of the target oil paper.

[0153] The second gray unit 12 is configured to determine a first gray value of a collected image based on a preset dark pixel area when frame transfer is performed on the collected image that produces a tailing effect; the dark pixel area is a region where a plurality of blocked pixels are located in an image imaging area corresponding to the collected image.

[0154] The state detection unit 13 is configured to determine the saturation state of the pixels of the acquisition image based on the first gray value and the second gray value.

[0155] In some embodiments, in the aspect of determining the first gray value of the acquisition image based on the preset dark pixel region when frame transferring the acquisition image that produces the tailing effect, the first gray unit 11 is specifically configured to:

[0156] acquire the gray value of each dark pixel in the dark pixel region when frame transferring the acquisition image;

[0157] determine the first gray value of the acquisition image based on the average gray value of each dark pixel corresponding to each row in the dark pixel region.

[0158] In some embodiments, in the aspect of determining the second gray value of the acquisition image based on the accumulated photoelectric charge of each pixel in the acquisition image after the frame transfer, the second gray unit 12 is specifically configured to:

[0159] acquire the exposure time of the acquisition image and the frame transfer time of the charge packet between adjacent pixels when frame transferring the acquisition image;

[0160] determine the second gray value of the acquisition image based on the accumulated photoelectric charge, the exposure time and the frame transfer time.

[0161] In some embodiments, in the aspect of determining the second gray value of the acquisition image based on the accumulated photoelectric charge, the exposure time and the frame transfer time, the second gray unit 12 is specifically configured to:

[0162] determine a transfer time factor of the frame transfer based on the exposure time and the frame transfer time;

[0163] determine the second gray value of the acquisition image based on the third gray value of the acquisition image corresponding to the accumulated photoelectric charge and the transfer time factor;

[0164] The second gray value of the acquisition image is used to represent the true gray value of the acquisition image in the case that the acquisition image produces the tailing effect, and the third gray value of the acquisition image is used to represent the original gray value of the acquisition image in the case that the acquisition image does not produce the tailing effect.

[0165] In some embodiments, in the aspect of determining the saturation state of the pixels of the acquisition image based on the first gray value and the second gray value, the state detection unit 13 is specifically further configured to:

[0166] determine, based on a difference between the second gray value and the third gray value, a loss gray value accumulated by each pixel of the acquisition image in the case of generating the smear effect;

[0167] determine, based on a size relationship between the first gray value and the loss gray value, a saturation state of the pixel of the acquisition image.

[0168] In some embodiments, in the aspect of determining the saturation state of the pixel of the acquisition image based on the size relationship between the first gray value and the loss gray value, the state detection unit 13 is specifically further configured to:

[0169] in response to the first gray value of the acquisition image being greater than the second gray value of the acquisition image, the saturation state of the pixel of the acquisition image is a saturated state;

[0170] in response to the first gray value of the acquisition image being less than or equal to the second gray value of the acquisition image, the saturation state of the pixel of the acquisition image is an unsaturated state.

[0171] Figure 10 is a performance decay identification device block diagram of a detector provided by an embodiment of the present application. Referring to Figure 10 The performance decay identification 10A of the detector includes a data acquisition unit 11A, a first identification unit 12A, and a second identification unit 13A.

[0172] The data acquisition unit 11A is configured to acquire a performance determination threshold of the detector and first and second gray values of an acquisition image. The performance determination threshold is used to represent the gray value of the pixel of the acquisition image when the performance of the detector is in a critical saturation state without decay. The first and second gray values of the acquisition image are obtained by using the detection method of the saturation state of the pixel in the above-mentioned embodiments.

[0173] The first identification unit 12A is configured to identify that the performance of the detector is negative decay if the first gray value is greater than the performance determination threshold when the first gray value of the acquisition image is greater than the second gray value of the acquisition image.

[0174] The second identification unit 13A is configured to identify that the performance of the detector is positive decay if the first gray value is less than the performance determination threshold when the first gray value of the acquisition image is greater than the second gray value of the acquisition image.

[0175] As to the specific manner in which each module performs operations in the device in the above-mentioned embodiments, the specific manner has been described in detail in the embodiments related to the method, and will not be described in detail here.

[0176] Figure 11 is a block diagram of an electronic device 20 according to an embodiment of the present application. For example, the electronic device 20 can be a server, an electronic component, or a server array, etc. Referring to Figure 10 , the electronic device 20 includes a processor 21, which can be a set of processors, which can include one or more processors, and a server 20 includes memory resources represented by a memory 22, in which a computer program, such as an application program, is stored. The computer program stored in the memory 22 can include one or more modules each corresponding to a set of executable instructions. In addition, the processing component 21 is configured to implement the method of detecting the pixel saturation state and / or the method of identifying the performance degradation of the detector as described above when executing the computer program.

[0177] In some embodiments, the electronic device 20 is a server, and the computing system in the server can run one or more operating systems, including any of the operating systems discussed above and any commercially available server operating system. The electronic device 20 can also run any of a variety of additional server applications and / or middleware applications, including an HTTP (HyperText Transfer Protocol) server, an FTP (File Transfer Protocol) server, a CGI (Common Gateway Interface) server, a hyper server, a database server, etc. Exemplary database servers include, but are not limited to, database servers available commercially from International Business Machines, etc.

[0178] In some embodiments, the processing component 21 generally controls the overall operations of the electronic device 20, such as operations associated with displaying, data processing, data communication, and recording operations. The processing component 21 can include one or more processors to execute computer programs to complete all or part of the steps of the above-described methods. In addition, the processing component 21 can include one or more modules to facilitate interaction between the processing component 21 and other components. For example, the processing component 21 can include a multimedia module to facilitate interaction between the user and the electronic device 20 and the processing component 21 using a multimedia component.

[0179] In some embodiments, the processor in processing component 21 can also be referred to as a CPU (Central Processing Unit). The processor can be an electronic chip with the processing capability of signals. The processor can also be a general-purpose processor, a digital signal processor (DSP), an application specific integrated circuit (ASIC), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic device, a discrete gate or transistor logic device, a discrete hardware component. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor or the like. In addition, the processor can be jointly implemented by integrated circuit chips.

[0180] In some embodiments, memory 22 is configured to store various types of data to support the operation of electronic device 20. Examples of these data include instructions for any application or method operating on electronic device 20, collected data, messages, pictures, videos, etc. Memory 22 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk, optical disk or graphene memory.

[0181] In some embodiments, memory 22 can be a memory stick, a TF card, etc., which can store all information in electronic device 20, including input raw data, computer programs, intermediate running results and final running results are saved in some embodiments, memory 22. It stores and retrieves information according to the location specified by the processor. With the in some embodiments, memory 22, the server 20 has memory function, so as to ensure normal work. The in some embodiments, memory 22 of electronic device 20 can be divided into main memory (memory) and auxiliary memory (external memory) according to the purpose, and there is also a classification method of external memory and internal memory. External memory is usually magnetic medium or optical disk, etc., which can save information for a long time. Memory refers to the storage component on the motherboard, which is used to store the data and programs currently being executed, but only for temporary storage of programs and data, and the data will be lost when the power is off or power is off.

[0182] In some embodiments, the electronic device 20 can further include a power supply component 23 configured to perform power management of the electronic device 20, a wired or wireless network interface 24 configured to connect the electronic device 20 to a network, and an input / output (I / O) interface 25. The electronic device 20 can operate based on an operating system stored in the memory 22, such as Windows Server, Mac OSX, Unix, Linux, FreeBSD, or the like.

[0183] In some embodiments, the power supply component 23 provides power to the various components of the electronic device 20. The power supply component 23 can include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power to the electronic device 20.

[0184] In some embodiments, the wired or wireless network interface 24 is configured to facilitate wired or wireless communication between the electronic device 20 and other devices. The electronic device 20 can access a wireless network based on a communication standard, such as WiFi, an operator network (e.g., 2G, 3G, 4G, or 5G), or a combination thereof.

[0185] In some embodiments, the wired or wireless network interface 24 receives broadcast signals or broadcast-related information from an external broadcast management system via a broadcast channel. In one example embodiment, the wired or wireless network interface 24 further includes a near field communication (NFC) module to facilitate short-range communication. For example, the NFC module can be implemented based on radio frequency identification (RFID) technology, infrared data association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology, and other technologies.

[0186] In some embodiments, the input / output (I / O) interface 25 provides an interface between the processing component 21 and peripheral interface modules, which can be a keypad, a click wheel, buttons, and the like. These buttons can include, but are not limited to, a home button, a volume button, a start button, and a lock button.

[0187] Figure 12 is a block diagram of a computer readable storage medium 30 provided by an embodiment of the present application. The computer readable storage medium 30 has stored thereon a computer program 31, wherein the computer program 31, when executed by a processor, implements the pixel saturation state detection method as described above, and / or the performance decay identification method of the detector.

[0188] The units integrated in each of the embodiments of the present application can be stored in the computer readable storage medium 30 if they are realized in the form of software function units and sold or used as independent products. Based on such understanding, the technical solutions of the present application essentially or the parts that make contributions to the prior art or the whole or part of the technical solutions can be embodied in the form of a software product. The computer readable storage medium 30 includes a computer program 31, which includes a plurality of instructions for causing a computer device (which can be a personal computer, a system server, or a network device, etc.), an electronic device (for example, MP3, MP4, etc., which can also be a smart terminal such as a mobile phone, a tablet computer, a wearable device, etc., or a desktop computer, etc.), or a processor to perform all or part of the steps of the method of each of the embodiments of the present application.

[0189] Figure 13 FIG. 4 is a block diagram of a computer program product 40 provided by an embodiment of the present application. The computer program product 40 includes program instructions 41, which can be executed by the processor of the server 20 to implement the detection method of the pixel saturation state and / or the performance degradation identification method of the detector as described above.

[0190] Those skilled in the art should understand that the embodiments of the present application can provide the detection method of the pixel saturation state, the performance degradation identification method of the detector, the detection device 10 of the pixel saturation state, the performance degradation identification device 10A of the detector, the electronic device 20, the computer readable storage medium 30, or the computer program product 40. Therefore, the present application can adopt a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can adopt the form of a computer program product 40 implemented on one or more computer program instructions 41 (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer usable program codes.

[0191] The present application is described with reference to the flowcharts and / or block diagrams according to the detection method of the pixel saturation state, the performance degradation identification method of the detector, the detection device 10 of the pixel saturation state, the performance degradation identification device 10A of the detector, the electronic device 20, the computer readable storage medium 30, or the computer program product 40 in the embodiments of the present application. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, and the combination of the flows and / or blocks in the flowcharts and / or block diagrams can be realized by the computer program product 40. These computer program products 40 can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to produce a machine, so that the program instructions 41 executed by the processor of the computer or other programmable data processing devices produce a method for implementing the steps of the flowcharts and / or block diagrams. Figure 1one or more processes and / or blocks Figure 1 an apparatus for performing the functions specified in the flowchart

[0192] These computer program products 40 can also be stored in a computer readable storage medium that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the program instructions stored in the computer program products 40 produce an article of manufacture including instructions which implement the flowchart Figure 1 one or more processes and / or blocks Figure 1 one or more blocks or steps

[0193] These program instructions 41 can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the program instructions 41 which execute on the computer or other programmable apparatus provide steps for implementing the flowchart Figure 1 one or more processes and / or blocks Figure 1 one or more blocks or steps

[0194] It should be noted that the various methods described above, apparatuses, electronic devices, computer readable storage media, computer program products, etc. can also include other implementations not expressly described above. The specific implementations described above are illustrative and the general principles described can be applied to other implementations as well. Thus, the general principles described above can be applied to other implementations as well without departing from the scope of the disclosure.

[0195] Other embodiments of the present disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the features of the present disclosure disclosed herein. It is intended that the present disclosure cover any and all variations of the present disclosure including those variations contained within the scope of the features of the present disclosure. It is intended that the specification and examples be considered as exemplary only, with the true scope and spirit of the disclosure being indicated by the following claims.

[0196] It is to be understood that the present disclosure is not limited to the precise construction described above and shown in the attached drawings, and that various modifications and changes can be made by those skilled in the art without departing from the scope of the present disclosure. The scope of the present disclosure is limited only by the claims that follow.

Claims

1. A method of detecting a saturation state of a pixel, characterized by, The method comprises: When frame transfer is performed on the collected image generating the tailing effect, a first gray value of the collected image is determined based on a preset dark pixel region; the dark pixel region is a region where a plurality of blocked pixels arranged in an image imaging area corresponding to the collected image are located; After the frame transfer, a second gray value of the collected image is determined based on the accumulated photoelectric charge amount of each pixel in the collected image, comprising: a transfer time factor of the frame transfer is determined based on the exposure time of the collected image and the frame transfer time of a charge packet between adjacent pixels when the frame transfer is performed on the collected image; the second gray value of the collected image is determined based on a third gray value of the collected image corresponding to the accumulated photoelectric charge amount and the transfer time factor; wherein the second gray value of the collected image is used to represent the real gray value of the collected image in the case that the collected image generates the tailing effect; the third gray value of the collected image is used to represent the original gray value of the collected image in the case that the collected image does not generate the tailing effect; Based on the first gray value and the second gray value, the pixel saturation state of the collected image is determined, comprising: based on the difference between the second gray value and the third gray value, the loss gray value accumulated by each pixel of the collected image in the case that the tailing effect is generated is determined; based on the size relationship between the first gray value and the loss gray value, the pixel saturation state of the collected image is determined; specifically comprising the following two items: In response to the first gray value of the collected image being greater than the second gray value of the collected image, the pixel saturation state of the collected image is saturated state; In response to the first gray value of the collected image being less than or equal to the second gray value of the collected image, the pixel saturation state of the collected image is unsaturated state.

2. The method of claim 1, wherein, The first gray value of the collected image is determined based on the preset dark pixel region when frame transfer is performed on the collected image generating the tailing effect, comprising: When the frame transfer is performed on the collected image, the gray value of each dark pixel in the dark pixel region is obtained; Based on the average gray value of each dark pixel corresponding to each row in the dark pixel region, the first gray value of the collected image is determined.

3. The method of claim 1, wherein, After the frame transfer, the second gray value of the collected image is determined based on the accumulated photoelectric charge amount of each pixel in the collected image, comprising: The exposure time of the collected image and the frame transfer time of a charge packet between adjacent pixels when the frame transfer is performed on the collected image are obtained; Based on the accumulated photoelectric charge amount, the exposure time and the frame transfer time, the second gray value of the collected image is determined.

4. A method of identifying performance degradation of a probe, characterized by, The method comprises: obtaining a performance determination threshold of the detector and a first gray value and a second gray value of the acquisition image; the performance determination threshold is used to represent the performance of the detector in the case of no decay, and to identify the gray value of the pixel of the acquisition image at the critical saturation; the first gray value and the second gray value of the acquisition image are obtained by using the pixel saturation state detection method in any one of claims 1-3; in the case that the first gray value of the acquisition image is greater than the second gray value of the acquisition image, if the first gray value is less than the performance determination threshold, it is identified that the performance of the detector is negative decay; or in the case that the first gray value of the acquisition image is greater than the second gray value of the acquisition image, if the first gray value is greater than the performance determination threshold, it is identified that the performance of the detector is positive decay.

5. A device for detecting a saturation state of a pixel, characterized by comprising: The device comprises: a first gray unit configured to determine a first gray value of the acquisition image based on a preset dark pixel region when frame transfer is performed on the acquisition image generating a tailing effect; the dark pixel region is a region where a plurality of blocked pixels are arranged in an image imaging area corresponding to the acquisition image; a second gray unit configured to determine a second gray value of the acquisition image based on the accumulated charge of each pixel in the acquisition image after the frame transfer; The second gray unit is specifically configured to determine a transfer time factor of the frame transfer based on the exposure time of the acquisition image and the frame transfer time of the charge packet between adjacent pixels when the frame transfer is performed on the acquisition image; determine the second gray value of the acquisition image based on the third gray value of the acquisition image corresponding to the accumulated charge and the transfer time factor; wherein the second gray value of the acquisition image is used to represent the true gray value of the acquisition image in the case that the acquisition image generates the tailing effect; the third gray value of the acquisition image is used to represent the original gray value of the acquisition image in the case that the acquisition image does not generate the tailing effect; a state detection unit configured to determine the saturation state of the pixels of the acquisition image based on the first gray value and the second gray value; The state detection unit is specifically configured to determine the loss gray value of each pixel of the acquisition image in the case of generating the tailing effect based on the difference between the second gray value and the third gray value; determine the saturation state of the pixels of the acquisition image based on the size relationship between the first gray value and the loss gray value; The state detection unit is specifically configured to respond to the case that the first gray value of the acquisition image is greater than the second gray value of the acquisition image, the saturation state of the pixels of the acquisition image is the saturated state; respond to the case that the first gray value of the acquisition image is less than or equal to the second gray value of the acquisition image, the saturation state of the pixels of the acquisition image is the unsaturated state. comprise:

6. An electronic device, comprising: a processor; a memory for storing executable instructions of the processor; ​ The processor is configured to execute the executable instructions to implement the detection method of the pixel saturation state as claimed in any one of claims 1 to 3, and / or the performance degradation identification method of the detector as claimed in claim 4.

7. A computer readable storage medium, comprising program data therein, wherein the program data comprises instructions operative to cause a computer to: receive a request for a resource from a client; determine whether the client is authorized to access the resource; and if the client is authorized to access the resource, provide the resource to the client. When the program data is executed by the processor of the electronic device, the electronic device is enabled to execute the detection method of the pixel saturation state as claimed in any one of claims 1 to 3, and / or the performance degradation identification method of the detector as claimed in claim 4.

Images