Image generation method and system for security screening system

Abstract

The present application relates to a kind of image generation method and system for security inspection system, belong to security imaging technical field, solve the problem that dirty map appears in security imaging in the prior art with the fluctuation of ray source and detector with time.The image generation method includes: the pixel value of all detector units on detector is sampled, as the original image data of current sampling;According to the original image data of current sampling, gain update array is updated, and updated gain update array is obtained;According to updated gain update array, gain data is updated, and updated gain data is obtained;According to updated gain data, the original image data of current sampling is gain corrected, and corrected image data is generated.Through the real-time updating of gain data in security inspection system, the appearance of dirty map is avoided, and the accuracy of security imaging is improved.

Description

Technical Field

[0001] This invention relates to the field of security inspection imaging technology, and in particular to an image generation method and system for security inspection systems. Background Technology

[0002] Currently, the most commonly used security screening method is X-ray security screening equipment, which is used to inspect passengers' luggage and belongings to check whether passengers and their luggage are carrying dangerous items such as firearms, ammunition, flammable, explosive, corrosive, toxic, or radioactive materials, in order to ensure the safety of aircraft and passengers' personal and property safety.

[0003] Currently, there are inconsistencies among the multiple detector units in the detector imaging process. These inconsistencies are mainly reflected in the differences in the dark current response of the detector units themselves in a dark field environment without radiation; and inconsistencies in the radiation response caused by differences in radiation distribution and inconsistencies between back-end electronic modules, which lead to bias correction and gain correction.

[0004] However, as time fluctuates, dirty images appear in security screening images, making it difficult for security personnel to identify them and reducing the accuracy of identification. Summary of the Invention

[0005] Based on the above analysis, the embodiments of the present invention aim to provide an image generation method and system for security inspection systems, in order to solve the problem of dirty images appearing in security inspection imaging due to the fluctuation of X-ray sources and detectors over time in the prior art.

[0006] On one hand, embodiments of the present invention provide an image generation method for a security inspection system, the image generation method comprising:

[0007] Acquire brightness field data from the detector, and obtain the gain update array and gain data based on the brightness field data;

[0008] After each acquisition of detector image data, the image data is corrected using the following method to generate a corrected image:

[0009] The pixel values ​​of all detector units on the detector are sampled and used as the raw image data for the current sampling.

[0010] The gain update array is updated based on the original image data of the current sampling to obtain the updated gain update array; the gain data is then updated based on the updated gain update array to obtain the updated gain data.

[0011] Gain correction is performed on the original image data of the current sampling based on the updated gain data to generate corrected image data.

[0012] Based on a further improvement of the above method, the step of obtaining the gain update array and gain data based on the brightness field data includes:

[0013] Acquire bright field data from the detector at M consecutive time points;

[0014] Take the data from the last K times out of M times as the gain update array;

[0015] Calculate the mean of the bright field data at M time points, and use it as the gain data.

[0016] A further improvement to the above method, wherein updating the gain update array based on the original image data of the current sampling to obtain the updated gain update array includes:

[0017] Sort all gain update data in the gain update array in chronological order, then delete the first gain update data to obtain the remaining K-1 gain update data;

[0018] The original image data of the current sampling is arranged at the end of the remaining K-1 gain update data to obtain the updated gain update array.

[0019] A further improvement to the above method, the step of updating the gain data according to the updated gain update array to obtain the updated gain data, includes:

[0020] Calculate the average of the K gain update data in the updated gain update array, and use it as temporary raw image data;

[0021]

[0022] Where W(i) represents the pixel value corresponding to the i-th detector unit in the temporary raw image data, i represents the index number of the detector unit, Tmp(i,j) represents the pixel value corresponding to the i-th detector unit in the j-th gain update data, and N represents the total number of detector units on the detector.

[0023] The gain data is updated based on the temporary original image data to obtain the updated gain data.

[0024] Based on the above method, and with further improvements, the gain data is updated using the temporary original image data in the following manner:

[0025] P2(i) = MAX(W(i), P(i));

[0026] Where P2(i) represents the pixel value corresponding to the i-th detector unit in the updated gain data, and P(i) represents the pixel value corresponding to the i-th detector unit in the unupdated gain data.

[0027] A further improvement to the above method, the update of gain data based on temporary original image data, includes:

[0028] Obtain standard gain data, first parameter, and second parameter; the standard gain data is the unupdated gain data directly calculated from the brightness field data.

[0029] The gain data is updated based on the temporary raw image data, standard gain data, the first parameter, and the second parameter.

[0030] A further improvement to the above method, the step of updating the gain data based on the temporary original image data, standard gain data, the first parameter, and the second parameter, includes:

[0031] When |P(i)-W(i)|<t1, and |(P1(i)-W(i)) / P1(i)|*100%<t2, then P2(i)=W(i); otherwise, P2(i)=P(i);

[0032] Where P(i) represents the pixel value corresponding to the i-th detector unit in the gain data, P1(i) represents the pixel value corresponding to the i-th detector unit in the standard gain data, P2(i) represents the pixel value corresponding to the i-th detector unit in the updated gain data, t1 represents the first parameter, and t2 represents the second parameter.

[0033] Based on further improvements to the above method, the first parameter and the second parameter satisfy the following conditions:

[0034] 0 < t1 < 100;

[0035] 0 < t² < 3%.

[0036] Based on the above method, a further improvement is made to the gain correction of the original image data of the current sampling using the following formula to generate the corrected image data:

[0037] S'(i)=(S(i)-offset(i))*V / (P2(i)-offset(i));

[0038] Where i represents the index number of the detector unit, S(i) represents the pixel value corresponding to the i-th detector unit in the original image data of the current sampling, S'(i) represents the pixel value corresponding to the i-th detector unit in the corrected image data, offset(i) represents the pixel value corresponding to the i-th detector unit in the pre-set dark field data, P2(i) represents the pixel value corresponding to the i-th detector unit in the updated gain data, and V represents the correction parameter.

[0039] On the other hand, embodiments of the present invention provide an image generation system for a security inspection system, the image generation system comprising:

[0040] The gain data acquisition module is used to obtain the gain update array and gain data based on the collected detector brightness field data.

[0041] The image data generation module is used to correct the image data after each acquisition of detector image data, and generate a corrected image in the following manner:

[0042] The pixel values ​​of all detector units on the detector are sampled and used as the raw image data for the current sampling.

[0043] The gain update array is updated based on the original image data of the current sampling to obtain the updated gain update array; the gain data is then updated based on the updated gain update array to obtain the updated gain data.

[0044] Gain correction is performed on the original image data of the current sampling based on the updated gain data to generate corrected image data.

[0045] Compared with the prior art, the present invention can achieve at least one of the following beneficial effects:

[0046] 1. By dynamically updating the gain data, the real-time accuracy of the gain data is determined, the accuracy of gain correction is improved, the occurrence of dirty images is avoided, and the accuracy of security inspection imaging is improved.

[0047] 2. There is no need to perform excessive image processing on the collected detector data to determine which areas are usable and which areas contain scanned objects. Only some detector units can be updated, not all detector units. Thus, gain data can be updated in real time without the need to update all detector units.

[0048] In this invention, the above-described technical solutions can be combined with each other to achieve more preferred combinations. Other features and advantages of this invention will be set forth in the following description, and some advantages may become apparent from the description or be learned by practicing the invention. The objects and other advantages of this invention can be realized and obtained from what is particularly pointed out in the description and drawings. Attached Figure Description

[0049] The accompanying drawings are for illustrative purposes only and are not intended to limit the invention. Throughout the drawings, the same reference numerals denote the same parts.

[0050] Figure 1 This is a flowchart illustrating an image generation method for a security inspection system provided in an embodiment of the present invention.

[0051] Figure 2 This is a schematic diagram of the structure of an image generation system for a security inspection system provided in an embodiment of the present invention. Detailed Implementation

[0052] Preferred embodiments of the present invention will now be described in detail with reference to the accompanying drawings, which form part of this application and are used together with the embodiments of the present invention to illustrate the principles of the present invention, but are not intended to limit the scope of the present invention.

[0053] A specific embodiment of the present invention discloses an image generation method for a security inspection system, such as... Figure 1 As shown, the image generation method includes:

[0054] S1: Collect the brightness field data of the detector, and obtain the gain update array and gain data based on the brightness field data;

[0055] S2: After each acquisition of detector image data, the image data is corrected in the following way to generate a corrected image:

[0056] S21: Sample the pixel values ​​of all detector units on the detector to use as the raw image data for the current sampling.

[0057] S22: Update the gain update array based on the original image data of the current sampling to obtain the updated gain update array; update the gain data based on the updated gain update array to obtain the updated gain data;

[0058] S23: Perform gain correction on the original image data of the current sampling based on the updated gain data to generate corrected image data.

[0059] Specifically, commonly used security inspection equipment employs a scanning structure of a radiation source and a line detector. The object is placed between the radiation source and the detector, which includes multiple detector units used to receive line data. The line data is then processed through gain correction to obtain a security inspection image.

[0060] Specifically, the radiation source can be a natural radiation source, such as cobalt-60 or cesium-137; or it can be an artificial radiation source, such as an X-ray source.

[0061] Specifically, the X-ray source and detector can remain stationary or undergo some form of relative motion. For example, in security screening equipment, the X-ray source and detector are fixed in the equipment, while the two are connected by a conveyor belt that moves the object. Since the movement of the conveyor belt has a consistent effect on the imaging, its influence can be ignored.

[0062] Specifically, in step S1, the bright field data of the detector is collected: the detector is turned on, and several sets of data are collected under the condition that there are no moving obstructions between the X-ray source and the detector; based on the collected sets of bright field data, the gain update array and gain data are obtained.

[0063] Preferably, obtaining the gain update array and gain data based on the brightness field data includes:

[0064] Acquire bright field data from the detector at M consecutive time points;

[0065] Take the data from the last K times out of M times as the gain update array;

[0066] Calculate the mean of the bright field data at M time points, and use it as the gain data.

[0067] Specifically, the detector collects bright field data at M consecutive time points to obtain M sets of bright field data. Each set of data includes the pixel values ​​of each detector unit. For example, if the detector has 400*400 detector units, then each set of data includes 160,000 pixel values.

[0068] Specifically, M sets of brightness field data from M consecutive time points are arranged in chronological order, and K sets of brightness field data from the K later time points are selected as the gain update array. Similarly, each set of data in the gain update array also includes 160,000 pixel values.

[0069] Specifically, M sets of brightness field data are collected at M time points, the average value of the M sets of brightness field data is calculated, and this average value is used as gain data for gain correction of the image data.

[0070] It is worth noting that after determining the above-mentioned gain update data and gain data, when the security inspection equipment starts the first security inspection imaging, the above-mentioned gain update array and gain data are used as the initial gain update array and gain data.

[0071] Specifically, in step S2, as the security inspection equipment continues to operate, image data is collected at preset times, and then the gain update array and gain data are continuously updated. Finally, gain correction is performed, and the gain-corrected image is displayed on the display device for security personnel to identify and confirm.

[0072] The image data collected at each moment is used to generate corrected image data through steps S21, S22 and S23.

[0073] Specifically, in step S21, at each preset time, the pixel values ​​of all detector units on the detector are collected, and the collected pixel values ​​of all detector units on the detector are used as the raw image data for the current sampling. For example, if the detector includes 160,000 detector units, then 1, 2, 3...160,000 are used as the index numbers of all detector units of the detector. It can be understood that the raw image data obtained in each sampling includes 160,000 pixel values.

[0074] Specifically, step S22 is as follows:

[0075] S221. Update the gain update array based on the original image data of the current sampling to obtain the updated gain update array;

[0076] S222. Update the gain data according to the updated gain update array to obtain the updated gain data.

[0077] Preferably, step S221 includes:

[0078] Sort all gain update data in the gain update array in chronological order, then delete the first gain update data to obtain the remaining K-1 gain update data;

[0079] The original image data of the current sampling is arranged at the end of the remaining K-1 gain update data to obtain the updated gain update array.

[0080] Specifically, the gain update array includes K gain update data. The gain update array is updated based on the original image data of the current sampling to obtain the updated gain update array.

[0081] It is understandable that if this sampling is the first sampling, the gain update array before the update is obtained from the brightness field data, as mentioned above, which is the data of the last K times out of M times; if this sampling is not the first sampling, the gain update array before the update is the gain update array after the previous sampling.

[0082] Arrange the K gain update data in the gain update array before the update in chronological order, then delete the gain update data that is the earliest in time, leaving K-1 gain update data. Finally, arrange the original image data of the current sampling at the end of the remaining K-1 gain update data to obtain the updated gain update array.

[0083] Understandably, the gain update array after each update still includes K gain update data.

[0084] By updating the gain update array in the above manner, the K gain update data included in the gain update array can be kept up-to-date, thereby reducing the error caused by the increase in the number of security checks.

[0085] Specifically, step S222 includes:

[0086] S2221. Calculate the average value of the K gain update data in the updated gain update array, and use it as temporary original image data;

[0087]

[0088] Where W(i) represents the pixel value corresponding to the i-th detector unit in the temporary raw image data, i represents the index number of the detector unit, Tmp(i,j) represents the pixel value corresponding to the i-th detector unit in the j-th gain update data, and N represents the total number of detector units on the detector.

[0089] S2222. Update the gain data based on the temporary original image data to obtain the updated gain data.

[0090] Specifically, the updated gain update array is obtained, and the average value of the included K gain update data is calculated. This average value is then used as the temporary raw image data. It is worth noting that the value of K is generally in the range of 10-20, because less computational resources are required within this range, and excellent security inspection image imaging results can be achieved.

[0091] For example, the detector includes 160,000 detector elements, N takes the value of 160,000, then i = 1, 2, 3... 160,000; the gain update array includes 15 gain update data, then K takes the value of 15, then j = 1, 2, 3... 15.

[0092] The pixel value corresponding to each detector element is calculated using the following formula:

[0093]

[0094] After obtaining 160,000 pixel values ​​for all detector units, the 160,000 pixel values ​​corresponding to all detector units are used as temporary raw image data.

[0095] Specifically, in step S22, the gain data is updated based on the temporary original image data to obtain the updated gain data.

[0096] It is understandable that if this sampling is the first sampling, the gain data before the update is derived from the brightness field data, as mentioned above, which is the average of the brightness field data at M time points; if this sampling is not the first sampling, the gain data before the update is the gain data after the previous sampling update.

[0097] Preferably, in one embodiment, the gain data is updated based on the temporary original image data in the following manner:

[0098] P2(i) = MAX(W(i), P(i));

[0099] Where P2(i) represents the pixel value corresponding to the i-th detector unit in the updated gain data, and P(i) represents the pixel value corresponding to the i-th detector unit in the unupdated gain data.

[0100] It is worth noting that as the number of samples taken by the security inspection equipment increases, the environment between the X-ray source and the detector changes continuously. To ensure that the environment of each detector unit at any given time remains consistent with the gain data acquired by the detector in step S1, the gain data is continuously updated in the following manner:

[0101] P2(i) = MAX(W(i), P(i));

[0102] Where P2(i) represents the pixel value corresponding to the i-th detector unit in the updated gain data, and P(i) represents the pixel value corresponding to the i-th detector unit in the unupdated gain data.

[0103] It is understandable that when there is an object between the detector and the radiation source, W(i) of the detector unit will be less than P(i), thus the pixel value corresponding to the detector unit will not be updated. Through the above-described gain data update method, it can be ensured that even if the environment changes, the updated gain data will be consistent with the gain data obtained in step S1 with a high probability.

[0104] Preferably, in another embodiment, updating the gain data based on the temporary original image data includes:

[0105] Obtain standard gain data, first parameter, and second parameter; the standard gain data is the unupdated gain data directly calculated from the brightness field data.

[0106] The gain data is updated based on the temporary raw image data, standard gain data, the first parameter, and the second parameter.

[0107] Specifically, the standard gain data is the unupdated gain data directly calculated from the brightness field data. It can be understood that this standard gain data can be obtained from M sets of brightness field data at M time points sampled in step S1.

[0108] Specifically, considering the normal fluctuations of the X-ray source and detector, if the value fluctuation of the pixel value corresponding to each detector unit is within the set range, the gain data can be updated.

[0109] Preferably, updating the gain data based on the temporary original image data, standard gain data, the first parameter, and the second parameter includes:

[0110] When |P(i)-W(i)|<t1, and |(P1(i)-W(i)) / P1(i)|*100%<t2, then P2(i)=W(i); otherwise, P2(i)=P(i);

[0111] Where P(i) represents the pixel value corresponding to the i-th detector unit in the gain data, P1(i) represents the pixel value corresponding to the i-th detector unit in the standard gain data, P2(i) represents the pixel value corresponding to the i-th detector unit in the updated gain data, t1 represents the first parameter, and t2 represents the second parameter.

[0112] Specifically, by setting update conditions for the gain data, where t1 and t2 are adjusted according to the specific conditions of the security inspection equipment, and the effect is better when t1 and t2 meet the following conditions:

[0113] 0 < t1 < 100;

[0114] 0 < t² < 3%.

[0115] It is worth noting that when |P(i)-W(i)|<t1 and |(P1(i)-W(i)) / P1(i)|*100%<t2, the gain data is updated, and the temporary original image data is used as the updated gain data.

[0116] Specifically, in step S23, gain correction is performed on the original image data of the current sampling based on the updated gain data to generate corrected image data. It is worth noting that after each sampling, the gain data corresponding to all detector units of the detector is updated according to steps S21 and S22. As can be seen from the set update conditions, the pixel value corresponding to each detector unit may be the pixel value corresponding to the gain data before the update, or it may be the pixel value corresponding to the temporary original image data. Furthermore, the image generation method for security inspection systems provided by this invention does not require extensive image processing of the collected detector data to determine which areas are usable or contain scanned objects; it can update only some detector units, rather than all detector units, thus achieving real-time update of gain data without the need to update all detector units.

[0117] Preferably, the gain correction of the original image data of the current sampling is performed using the following formula to generate the corrected image data:

[0118] S'(i)=(S(i)-offset(i))*V / (P2(i)-offset(i));

[0119] Where i represents the index number of the detector unit, S(i) represents the pixel value corresponding to the i-th detector unit in the original image data of the current sampling, S'(i) represents the pixel value corresponding to the i-th detector unit in the corrected image data, offset(i) represents the pixel value corresponding to the i-th detector unit in the pre-set dark field data, P2(i) represents the pixel value corresponding to the i-th detector unit in the updated gain data, and V represents the correction parameter.

[0120] It is worth noting that in step S23, the gain correction of the original image data of the current sampling is performed based on the updated gain data to generate corrected image data. The corrected image data can be displayed on a visualization device for security personnel to identify and confirm.

[0121] It is understandable that the pre-set dark field data is data collected under the condition that the X-ray source is not turned on and there are no moving obstructions between the X-ray source and the detector. Each dark field data includes the pixel values ​​corresponding to all detector units.

[0122] Another specific embodiment of the present invention discloses an image generation system for a security inspection system, such as... Figure 2 As shown, the image generation system includes:

[0123] The gain data acquisition module 201 is used to obtain the gain update array and gain data based on the acquired detector brightness field data;

[0124] The image data generation module 202 is used to correct the image data after each acquisition of detector image data in the following manner to generate a corrected image:

[0125] The pixel values ​​of all detector units on the detector are sampled and used as the raw image data for the current sampling.

[0126] The gain update array is updated based on the original image data of the current sampling to obtain the updated gain update array; the gain data is then updated based on the updated gain update array to obtain the updated gain data.

[0127] Gain correction is performed on the original image data of the current sampling based on the updated gain data to generate corrected image data.

[0128] Compared with existing technologies, the image generation method and system for security inspection systems provided in this embodiment determine the real-time accuracy of gain data by dynamically updating gain data, thereby improving the accuracy of gain correction, avoiding the occurrence of dirty images, and improving the accuracy of security inspection imaging. At the same time, it eliminates the need for extensive image processing of the collected detector data to determine which areas are usable and which areas contain scanned objects, allowing for the updating of only some detector units instead of all detector units. This enables real-time updating of gain data even without the need to update all detector units.

[0129] Those skilled in the art will understand that all or part of the processes of the methods described in the above embodiments can be implemented by a computer program instructing related hardware, and the program can be stored in a computer-readable storage medium. The computer-readable storage medium may be a disk, optical disk, read-only memory, or random access memory, etc.

[0130] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the scope of protection of the present invention.

Claims

1. An image generation method for a security inspection system, characterized in that, The image generation method includes: Acquire brightness field data from the detector, and obtain the gain update array and gain data based on the brightness field data, which serve as the initial gain update array and gain data; After each acquisition of detector image data, the image data is corrected using the following method to generate a corrected image: The pixel values ​​of all detector units on the detector are sampled and used as the raw image data for the current sampling. The gain update array is updated based on the original image data of the current sampling to obtain the updated gain update array; the gain data is then updated based on the updated gain update array to obtain the updated gain data. Gain correction is performed on the original image data of the current sampling based on the updated gain data to generate corrected image data; The gain update array and gain data obtained based on the brightness field data include: Acquire bright field data from the detector at M consecutive time points; Take the data from the last K times out of M times as the gain update array; Calculate the mean of the bright field data at M time points, and use it as the gain data; The step of updating the gain update array based on the original image data of the current sampling to obtain the updated gain update array includes: Sort all gain update data in the gain update array in chronological order, then delete the first gain update data to obtain the remaining K-1 gain update data; The original image data of the current sampling is arranged at the end of the remaining K-1 gain update data to obtain the updated gain update array; The step of updating the gain data according to the updated gain update array to obtain the updated gain data includes: Calculate the average of the K gain update data in the updated gain update array, and use it as temporary original image data; Where W(i) represents the pixel value corresponding to the i-th detector unit in the temporary raw image data, i represents the index number of the detector unit, Tmp(i,j) represents the pixel value corresponding to the i-th detector unit in the j-th gain update data, and N represents the total number of detector units on the detector. The gain data is updated based on the temporary original image data to obtain the updated gain data.

2. The image generation method according to claim 1, characterized in that, Based on the temporary original image data, the gain data is updated in the following way: P2(i) = MAX(W(i), P(i)); Where P2(i) represents the pixel value corresponding to the i-th detector unit in the updated gain data, and P(i) represents the pixel value corresponding to the i-th detector unit in the unupdated gain data.

3. The image generation method according to claim 1, characterized in that, The update of gain data based on temporary original image data includes: Obtain standard gain data, first parameter, and second parameter; the standard gain data is the unupdated gain data directly calculated from the brightness field data. The gain data is updated based on the temporary original image data, standard gain data, the first parameter, and the second parameter.

4. The image generation method according to claim 3, characterized in that, The step of updating the gain data based on the temporary original image data, standard gain data, the first parameter, and the second parameter includes: When |P(i)-W(i)|<t1, and |(P1(i)-W(i)) / P1(i)|*100%<t2, then P2(i)=W(i); otherwise, P2(i)=P(i); Where P(i) represents the pixel value corresponding to the i-th detector unit in the gain data, P1(i) represents the pixel value corresponding to the i-th detector unit in the standard gain data, P2(i) represents the pixel value corresponding to the i-th detector unit in the updated gain data, t1 represents the first parameter, and t2 represents the second parameter.

5. The image generation method according to claim 4, characterized in that, The first and second parameters must satisfy the following conditions: 0＜t1＜100； 0＜t2＜3％。 6. The image generation method according to claim 1, characterized in that, Gain correction is performed on the original image data of the current sampling using the following formula to generate the corrected image data: S′(i)=(S(i)-offset(i))*V / (P2(i)-offset(i)); Where i represents the index number of the detector unit, S(i) represents the pixel value corresponding to the i-th detector unit in the original image data of the current sampling, S'(i) represents the pixel value corresponding to the i-th detector unit in the corrected image data, offset(i) represents the pixel value corresponding to the i-th detector unit in the pre-set dark field data, P2(i) represents the pixel value corresponding to the i-th detector unit in the updated gain data, and V represents the correction parameter.

7. An image generation system for a security inspection system, characterized in that, The image generation system includes: The gain data acquisition module is used to obtain the gain update array and gain data based on the acquired detector brightness field data, which serve as the initial gain update array and gain data. The image data generation module is used to correct the image data after each acquisition of detector image data, and generate a corrected image in the following manner: The pixel values ​​of all detector units on the detector are sampled and used as the raw image data for the current sampling. The gain update array is updated based on the original image data of the current sampling to obtain the updated gain update array; the gain data is then updated based on the updated gain update array to obtain the updated gain data. Gain correction is performed on the original image data of the current sampling based on the updated gain data to generate corrected image data; The gain update array and gain data obtained based on the collected detector brightness field data include: Acquire bright field data from the detector at M consecutive time points; Take the data from the last K times out of M times as the gain update array; Calculate the mean of the bright field data at M time points, and use it as the gain data; The step of updating the gain update array based on the original image data of the current sampling to obtain the updated gain update array includes: Sort all gain update data in the gain update array in chronological order, then delete the first gain update data to obtain the remaining K-1 gain update data; The original image data of the current sampling is arranged at the end of the remaining K-1 gain update data to obtain the updated gain update array; The step of updating the gain data according to the updated gain update array to obtain the updated gain data includes: Calculate the average of the K gain update data in the updated gain update array, and use it as temporary original image data; Where W(i) represents the pixel value corresponding to the i-th detector unit in the temporary raw image data, i represents the index number of the detector unit, Tmp(i,j) represents the pixel value corresponding to the i-th detector unit in the j-th gain update data, and N represents the total number of detector units on the detector. The gain data is updated based on the temporary original image data to obtain the updated gain data.

Images