Infrared baffle-less method and system based on temperature correction

Abstract

This invention provides a temperature-corrected infrared diaphragmless method and system. The method includes the following steps: Step S1: Acquiring background data using a multi-segment, multi-background model without a diaphragm; Step S2: Acquiring focal plane temperature using single-frame averaging and multi-frame smoothing; Step S3: Calculating weighting coefficients using a mean + distance weighting method; Step S4: Calculating the weighting. This invention's temperature-corrected diaphragmless technology significantly improves detector non-uniformity, resulting in image quality superior to traditional two-point correction and multi-segment, multi-background correction. This invention solves the problem of image obstruction caused by diaphragms. Furthermore, this invention allows for the use of an external temperature sensor instead of a temperature-compensated detector, making the method highly versatile and easy to implement in engineering.

Description

Technical Field

[0001] This invention relates to the technical field of infrared imaging, and more specifically, to a temperature-corrected infrared baffleless method and system. Background Technology

[0002] Due to defects in the materials used, non-uniformity of doping, and instability in the manufacturing process, different pixels in an infrared focal plane array can exhibit different output signal amplitudes under the same uniform incident radiation; this is known as the non-uniformity of the infrared focal plane array response. The causes of non-uniformity are complex. Generally, the main reasons we understand are due to inhomogeneities in the semiconductor materials used in the fabrication (impurity concentration, crystal defects, inhomogeneities in the internal structure), mask errors, defects, and process conditions. Simultaneously, it is also the result of a combination of factors, including the infrared sensing element, readout circuitry, semiconductor characteristics, and amplification circuitry.

[0003] Infrared image non-uniformity correction is a crucial step in infrared image processing, determining the overall image quality of infrared cameras. In engineering applications, commonly used correction methods include two-point correction and multi-segment multi-background correction.

[0004] Between cooled and uncooled detectors, cooled detectors have a smaller NETD (noise equivalent temperature difference) (usually less than 20 mK), and can achieve good results using common two-point correction and multi-segment multi-background correction methods. Uncooled detectors, on the other hand, have a larger NETD (usually greater than 40 mK), and the above methods cannot achieve good results. Furthermore, uncooled detectors are divided into those with semiconductor coolers and those without. For detectors without semiconductor coolers, as the focal plane temperature rises, the non-uniformly acquired multi-segment background data cannot meet the requirements.

[0005] Therefore, a technical solution is needed to improve the above-mentioned technical problems. Summary of the Invention

[0006] In view of the deficiencies in the prior art, the purpose of this invention is to provide an infrared baffle-less method and system based on temperature correction.

[0007] According to the present invention, an infrared baffle-less method based on temperature correction is provided, the method comprising the following steps:

[0008] Step S1: Use a multi-segment, multi-background data acquisition system without baffles to collect background data;

[0009] Step S2: Collect focal plane temperature by averaging across single frames and smoothing across multiple frames;

[0010] Step S3: Calculate the weighting coefficients using the mean + distance weighting method;

[0011] Step S4: Calculate the weighting, perform two-point correction, and complete the non-uniformity correction.

[0012] Preferably, step S1 includes the following steps:

[0013] Step S1.1: Configure the gain of the uncooled detector to three levels: low temperature, normal temperature, and high temperature.

[0014] Step S1.2: Set the ambient temperature to -40℃ to +60℃, with three settings;

[0015] Step S1.3: Collect N1, N2, and N3 background data within the three temperature ranges. After setting the temperature in the high and low temperature chamber, keep it warm for a period of time, and then cover the detector with a uniform baffle to collect data.

[0016] Preferably, step S2 includes the following steps:

[0017] Step S2.1: Sum the values ​​of the focal plane temperature points within a single frame, and then divide by the total number of focal plane temperature points;

[0018] Step S2.2: Multi-frame smoothing is achieved by iteratively calculating the average value.

[0019] Preferably, in step S3, the focal plane temperature of a certain interval is divided into N equal parts, the weighted values ​​are calculated, and then the distance weight rule is adopted for design. When the real-time focal plane temperature falls in interval 1, the weights are w1 = (N-1) / N and w2 = 1 / N; when the real-time focal plane temperature falls in interval 2, the weights are w1 = (N-2) / N and w2 = 2 / N; when the real-time focal plane temperature falls in interval 3, the weights are w1 = (N-3) / N and w2 = 3 / N; and so on. When the real-time focal plane temperature falls in interval N, the weights are w1 = 1 / N and w2 = (N-1) / N.

[0020] Preferably, the weighted background calculation formula in step S4 is as shown in equation (1.3), and then two-point correction is performed to complete the non-uniformity correction:

[0021] B = Bn-1*W1 + Bn*W2 (1.3)

[0022] The present invention also provides a temperature-corrected infrared baffle-less system, the system comprising the following modules:

[0023] Module M1: Employs a multi-segment, multi-background data acquisition system without baffle plates;

[0024] Module M2: Employs single-frame averaging and multi-frame smoothing to acquire focal plane temperature;

[0025] Module M3: Calculates weighting coefficients using a weighting system based on mean and distance;

[0026] Module M4: Calculates weights, performs two-point correction, and completes non-uniformity correction.

[0027] Preferably, module M1 includes the following modules:

[0028] Module M1.1: Configures the gain of the uncooled detector to three levels: low temperature, normal temperature, and high temperature.

[0029] Module M1.2: Sets the ambient temperature to -40℃ to +60℃, with three settings.

[0030] Module M1.3: Collects N1, N2, and N3 background data within three temperature ranges. After setting the temperature in the high and low temperature chamber and maintaining the temperature for a period of time, the detector is covered with a uniform baffle for data acquisition.

[0031] Preferably, module M2 includes the following modules:

[0032] Module M2.1: Sum the values ​​of the focal plane temperature points within a single frame, and then divide by the total number of focal plane temperature points;

[0033] Module M2.2: Multi-frame smoothing is achieved through a system that calculates the mean value using a loop.

[0034] Preferably, module M3 divides the focal plane temperature of a certain interval into N equal parts, calculates the weighted values, and then designs the weighted values ​​according to the distance weighting rule. When the real-time focal plane temperature falls in interval 1, the weights are w1 = (N-1) / N and w2 = 1 / N; when the real-time focal plane temperature falls in interval 2, the weights are w1 = (N-2) / N and w2 = 2 / N; when the real-time focal plane temperature falls in interval 3, the weights are w1 = (N-3) / N and w2 = 3 / N; and so on. When the real-time focal plane temperature falls in interval N, the weights are w1 = 1 / N and w2 = (N-1) / N.

[0035] Preferably, the weighted background calculation formula for module M4 is as shown in equation (1.3), and then two-point correction can be performed to complete the non-uniformity correction:

[0036] B = Bn-1*W1 + Bn*W2 (1.3)

[0037] Compared with the prior art, the present invention has the following beneficial effects:

[0038] 1. The present invention is based on temperature correction without baffle technology, which greatly improves the non-uniformity of the detector, making the image quality superior to traditional two-point correction and multi-segment multi-background correction.

[0039] 2. This invention solves the problem of images being obscured by a baffle;

[0040] 3. This invention can use an external temperature sensor to replace a temperature-compensated detector, making this method more versatile and easier to implement in engineering. Attached Figure Description

[0041] Other features, objects, and advantages of the present invention will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings:

[0042] Figure 1 The graph shows the response curves of each pixel and the normalized response curve of this invention.

[0043] Figure 2 This is a schematic diagram illustrating the principle of multi-segment multi-background correction in this invention;

[0044] Figure 3 This is a graph showing the corresponding curves of the detector of the present invention;

[0045] Figure 4 This is a process diagram of the multi-segment, multi-background correction of the present invention;

[0046] Figure 5 This is a calculation diagram of the focal plane temperature smoothing in this invention;

[0047] Figure 6 This is a focal plane temperature acquisition diagram of the present invention;

[0048] Figure 7 This is a focal plane temperature weighted graph of the present invention;

[0049] Figure 8 This is a rendering of the invention. Detailed Implementation

[0050] The present invention will now be described in detail with reference to specific embodiments. These embodiments will help those skilled in the art to further understand the present invention, but do not limit the invention in any way. It should be noted that those skilled in the art can make several changes and improvements without departing from the concept of the present invention. These all fall within the scope of protection of the present invention.

[0051] Example 1:

[0052] According to the present invention, an infrared baffle-less method based on temperature correction is provided, the method comprising the following steps:

[0053] Step S1: Use a multi-segment, multi-background data acquisition system without baffles to collect background data;

[0054] Step S1.1: Configure the gain of the uncooled detector to three levels: low temperature, normal temperature, and high temperature.

[0055] Step S1.2: Set the ambient temperature to -40℃ to +60℃, with three settings;

[0056] Step S1.3: Collect N1, N2, and N3 background data within the three temperature ranges. After setting the temperature in the high and low temperature chamber, keep it warm for a period of time, and then cover the detector with a uniform baffle to collect data.

[0057] Step S2: Collect focal plane temperature by averaging across single frames and smoothing across multiple frames;

[0058] Step S2.1: Sum the values ​​of the focal plane temperature points within a single frame, and then divide by the total number of focal plane temperature points;

[0059] Step S2.2: Multi-frame smoothing is achieved by iteratively calculating the average value.

[0060] Step S3: Calculate the weighting coefficients using the mean + distance weighting method; divide the focal plane temperature of a certain interval into N equal parts, calculate the weighting values, and then design the weighting using the distance weighting rule. When the real-time focal plane temperature falls in interval 1, the weights are w1 = (N-1) / N, w2 = 1 / N; when the real-time focal plane temperature falls in interval 2, the weights are w1 = (N-2) / N, w2 = 2 / N; when the real-time focal plane temperature falls in interval 3, the weights are w1 = (N-3) / N, w2 = 3 / N; and so on. When the real-time focal plane temperature falls in interval N, the weights are w1 = 1 / N, w2 = (N-1) / N.

[0061] Step S4: Calculate the weighted average, perform two-point correction, and complete the non-uniformity correction; the formula for calculating the weighted background is as shown in equation (1.3), and then the non-uniformity correction can be completed by performing two-point correction:

[0062] B = Bn-1*W1 + Bn*W2 (1.3)

[0063] Example 2:

[0064] Example 2 is a preferred embodiment of Example 1, and is used to illustrate the present invention in more detail.

[0065] The present invention also provides a temperature-corrected infrared baffle-less system, the system comprising the following modules:

[0066] Module M1: Employs a multi-segment, multi-background data acquisition system without baffle plates;

[0067] Module M1.1: Configures the gain of the uncooled detector to three levels: low temperature, normal temperature, and high temperature.

[0068] Module M1.2: Sets the ambient temperature to -40℃ to +60℃, with three settings.

[0069] Module M1.3: Collects N1, N2, and N3 background data within three temperature ranges. After setting the temperature in the high and low temperature chamber and maintaining the temperature for a period of time, the detector is covered with a uniform baffle for data acquisition.

[0070] Module M2: Employs single-frame averaging and multi-frame smoothing to acquire focal plane temperature;

[0071] Module M2.1: Sum the values ​​of the focal plane temperature points within a single frame, and then divide by the total number of focal plane temperature points;

[0072] Module M2.2: Multi-frame smoothing is achieved through a system that calculates the mean value using a loop.

[0073] Module M3: The weighting coefficients are calculated using a weighting system based on the mean and distance. The focal plane temperature of a certain interval is divided into N equal parts. The weighting values ​​are calculated, and then the distance weighting rule is applied. When the real-time focal plane temperature falls in interval 1, the weights are w1 = (N-1) / N and w2 = 1 / N; when the real-time focal plane temperature falls in interval 2, the weights are w1 = (N-2) / N and w2 = 2 / N; when the real-time focal plane temperature falls in interval 3, the weights are w1 = (N-3) / N and w2 = 3 / N; and so on. When the real-time focal plane temperature falls in interval N, the weights are w1 = 1 / N and w2 = (N-1) / N.

[0074] Module M4: Calculate the weighted average, perform two-point correction, and complete the non-uniformity correction; the weighted background calculation formula is as shown in equation (1.3), and then the non-uniformity correction can be completed by performing two-point correction:

[0075] B = Bn-1*W1 + Bn*W2 (1.3)

[0076] Example 3:

[0077] Example 3 is a preferred example of Example 1, and is used to illustrate the present invention in more detail.

[0078] This invention relates to the fields of FPGA, infrared imaging, non-uniformity correction, weighted background, and baffle-less technology. Based on two-point correction and multi-segment multi-background correction methods, this invention utilizes a distance-weighted method with background mean corrected by focal plane temperature or an external temperature sensor to solve the non-uniformity problem caused by the temperature rise of the focal plane in uncooled detectors. This method is applicable to uncooled detectors with semiconductor coolers, uncooled detectors without semiconductor coolers, and cooled detectors, etc.

[0079] Two-point correction:

[0080] The two-point correction method is a relatively simple and computationally inexpensive correction method, but it is the most widely used. Assuming that the response characteristics of each pixel in the focal plane array change linearly within a certain range and are time-stable, the response characteristics of each pixel in the focal plane can be expressed as equation (1.1):

[0081]

[0082] In the formula K is the input irradiance of the detection unit. ij Q is the gain coefficient or slope of the characteristic curve of the detection unit response. ij is the offset or the intercept of the characteristic curve, i is the detector output array, and j is the detector output array, and j is the vertical coordinate.

[0083] Because of K ij and Q ij The difference in response of each pixel to the same input radiation intensity. Different, such as Figure 1 As shown in the figure, the horizontal axis represents temperature, the vertical axis represents the response value of each pixel on the focal plane, TL represents temperature point TL, TH represents temperature point TH, and the multiple slopes refer to the curves of the response of different pixel points.

[0084] By using a linear transformation method, the response curves of each pixel are normalized, such as... Figure 1 As shown, two-point correction can be achieved. The linear transformation model can be expressed as equation (1.2):

[0085]

[0086] Among them, y ij (φ) represents the response output; G ij Indicates the gain parameter; O ij This represents the bias parameter.

[0087] Multi-segment, multi-background correction:

[0088] This correction method makes full use of the changes in the detector's response rate at different integration times, so that each integration time corresponds to a relatively large temperature range. Then, the large temperature range corresponding to each integration time is further subdivided, and finally, each relatively large temperature range is further subdivided into smaller temperature ranges.

[0089] The specific implementation process is as follows: Figure 2 In the figure, the horizontal axis represents temperature; the vertical axis represents detector response; a, b, and c describe the response curves of three pixels in the detector; T1, T2, T3, and T4 represent four temperature points; and the dashed lines represent the response values ​​of each pixel in the detector after calibration.

[0090] Suppose there are N integration times, and each integration time is divided into M temperature ranges. Then the number of temperature ranges is K = M × N. Next, each of the final K temperature ranges is assigned a temperature setting T. ki1 and T ki2 Perform two-point correction on the blackbody to generate T. ki1 ~T ki2 Correction factor k within the temperature range i and using T ki1 The background produced by the blackbody is b i b represents the baseline data used for correction; ultimately, a total of k sets of correction factors k corresponding to k temperature ranges are generated. i and b i The data is then stored in memory. When observing a specific target, the system automatically obtains the current target irradiance and background irradiance (b). i Compare the results and use the k that best matches the current target. i and b i Non-uniformity correction is performed, which allows it to better adapt to target observation over a wider temperature range.

[0091] Background mean and distance-weighted correction based on focal plane temperature or temperature transfer correction:

[0092] Take an uncooled detector without a semiconductor cooler as an example:

[0093] 1. Baseline data collection:

[0094] Based on the compensation method, models using multiple shutters and multiple bases can be divided into built-in shutter models and models without shutters.

[0095] Built-in shutter models insert a small, blackened aluminum plate (commonly known as a shutter plate) into the optical path. A DC motor controls the shutter plate's entry and exit from the optical path. Once inside the optical path, the shutter plate blocks incident radiation, so the detector only receives radiation from its surface. If the shutter plate is relatively uniform, compensation can be applied to improve image quality. After exiting the optical path, the detector can receive external radiation for real-time imaging. The biggest drawback is that during the correction process, the image is frozen, and the target is lost, making it unsuitable for high-real-time scenarios such as observation and tracking.

[0096] Cameras without shutters do not require a physical shutter structure; they directly utilize image algorithms to correct the image background. They offer greater versatility but are technically challenging to implement. This invention employs camera technology without shutters.

[0097] First, the gain of the uncooled detector is configured with three levels: low temperature, normal temperature, and high temperature. According to... Figure 3Based on the detector's corresponding curve, the ambient temperature was set to -40℃ to +60℃. The temperature ranges are divided as follows: Low temperature range: -40℃ to -25℃; Low temperature range: -25℃ to +20℃; Low temperature range: +20℃ to +60℃. Note that the temperature range divisions may differ for different detectors; adjustments will be made accordingly. Figure 3 In the diagram, the horizontal axis represents temperature in degrees Celsius, and the vertical axis represents the detector's output analog voltage in millivolts.

[0098] Then, within the three gear ranges, N1, N2, and N3 baseline data points are collected, such as... Figure 4 Specifically, a background temperature reading can be collected every 3-5°C. In general, the temperature range should be covered from -40°C to +60°C, ensuring the detector collects background data across the entire temperature range. The background temperature measurement process involves setting the temperature in the high and low temperature chamber and maintaining it for a period of time. Then, a uniform baffle is placed over the detector to collect data. Figure 4 The classification of low temperature, normal temperature, and high temperature ranges is based on... Figure 3 The slope division of the corresponding curve of the detector. For example... Figure 3 Medium and low temperatures: -40 to -10°C; normal temperatures: -10 to +40°C; high temperatures: +40 to +60°C. The horizontal axis represents temperature; N1, N2, and N3 correspond to N background data points collected in the low temperature, normal temperature, and high temperature ranges, respectively. Figure 4 The background data used in this invention are multi-segment background data.

[0099] 2. Focal plane temperature acquisition:

[0100] The focal plane temperature of an uncooled detector without a semiconductor cooler varies with the ambient temperature, and the detector's response value also changes accordingly. A one-to-one correspondence can be established between the focal plane temperature and the background temperature. Then, the corresponding background temperature can be looked up using the focal plane temperature for calibration.

[0101] The focal plane temperature should not change too much; if the change is too large, it will cause a jump in the selected background, resulting in flickering after image correction. Therefore, the focal plane temperature needs to be collected and processed.

[0102] The present invention acquires focal plane temperature by means of single-frame averaging and multi-frame smoothing.

[0103] The average value for a single frame is easy to understand: sum the values ​​of the focal plane temperature points within a single frame and then divide by the total number of focal plane temperature points.

[0104] Multi-frame smoothing can be achieved, for example, by selecting N=64 frames and using a cyclical averaging method. Figure 5As shown, the average value of the first output frame is obtained by calculating the average value of frames 1 to 64, the average value of the second output frame is obtained by calculating the average value of frames 2 to 65, the average value of the third output frame is obtained by calculating the average value of frames 3 to 66, and so on.

[0105] 3. Weighting coefficients:

[0106] The weighting coefficients were calculated using a weighting method that combines the mean and distance.

[0107] Above, we collected N = N1 + N2 + N3 background data points and established a one-to-one correspondence between the focal plane temperature and the background data. Note: The focal plane temperature should be collected simultaneously with the background data, such as... Figure 6 As shown.

[0108] Once an infrared detector is assembled into a complete unit, its focal plane temperature will inevitably fall within a certain range during use. Taking a specific range as an example, the weighted calculation process will be explained.

[0109] like Figure 7 As shown, the focal plane temperature (F1-F2) of a certain interval is divided into N equal parts (usually N=8), and the weighted values ​​are calculated. Then, the design is carried out using the distance weight rule. When the real-time focal plane temperature falls in interval 1, the weights are w1=(N-1) / N, w2=1 / N; when the real-time focal plane temperature falls in interval 2, the weights are w1=(N-2) / N, w2=2 / N; when the real-time focal plane temperature falls in interval 3, the weights are w1=(N-3) / N, w2=3 / N; and so on. When the real-time focal plane temperature falls in interval N, the weights are w1=1 / N, w2=(N-1) / N.

[0110] 4. Weighted calculation:

[0111] The final background calculation formula is shown in equation (1.3), and then two-point correction can be performed to complete the non-uniformity correction:

[0112] B = Bn-1*W1 + Bn*W2 (1.3)

[0113] Where B represents the final corrected baseline data; Bn-1 and Bn refer to Figure 4 Two adjacent baseline data points in any interval of the data.

[0114] Figure 8 The images show the results of conventional two-point correction (2 hours of stress testing) and background weight correction (2 hours of stress testing). Using the conventional two-point correction algorithm, the detector's response deviates from the acquired background data as the focal plane temperature changes, resulting in inconsistent image uniformity. The focal temperature weighted multi-interval background correction method of this invention makes the corrected background data change with the focal temperature, resulting in better performance.

[0115] 5. Versatility:

[0116] For both uncooled and cooled detectors with semiconductor coolers, these detectors have temperature compensation capabilities, and the focal plane temperature is a fixed value. In this case, an external temperature sensor can be used instead of the focal plane temperature for weighted background calculation.

[0117] This invention utilizes temperature compensation to correct the background.

[0118] Those skilled in the art can understand this embodiment as a more specific description of Embodiment 1 and Embodiment 2.

[0119] Those skilled in the art will understand that, besides implementing the system and its various devices, modules, and units provided by this invention in the form of purely computer-readable program code, the same functions can be achieved entirely through logical programming of the method steps, making the system and its various devices, modules, and units of this invention function in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers. Therefore, the system and its various devices, modules, and units provided by this invention can be considered as a hardware component, and the devices, modules, and units included therein for implementing various functions can also be considered as structures within the hardware component; alternatively, the devices, modules, and units for implementing various functions can be considered as both software modules implementing the method and structures within the hardware component.

[0120] Specific embodiments of the present invention have been described above. It should be understood that the present invention is not limited to the specific embodiments described above, and those skilled in the art can make various changes or modifications within the scope of the claims, which do not affect the essence of the present invention. Unless otherwise specified, the embodiments and features described in this application can be arbitrarily combined with each other.

Claims

1. A temperature-corrected infrared baffleless method, characterized in that, The method includes the following steps: Step S1: Use a multi-segment, multi-background data acquisition system without baffles to collect background data; Step S2: Collect focal plane temperature by averaging across single frames and smoothing across multiple frames; Step S3: Calculate the weighting coefficients using the mean + distance weighting method; Step S4: Calculate the weighted average, perform two-point correction, and complete the non-uniformity correction; Step S1 includes the following steps: Step S1.1: Configure the gain of the uncooled detector to three levels: low temperature, normal temperature, and high temperature. Step S1.2: Set the ambient temperature to -40℃ to +60℃, with three settings; Step S1.3: Collect N1, N2, and N3 background data within the three temperature ranges. After setting the temperature in the high and low temperature chamber, keep it warm for a period of time. Cover the detector with a uniform baffle to collect data. N1, N2, and N3 correspond to the N background data collected in the low temperature, room temperature, and high temperature ranges, respectively. Step S2 includes the following steps: Step S2.1: Sum the values ​​of the focal plane temperature points within a single frame, and then divide by the total number of focal plane temperature points; Step S2.2: Multi-frame smoothing is achieved by iteratively calculating the average value; Step S3 divides the focal plane temperature of a certain interval into N equal parts, calculates the weighted values, and then designs the weighted values ​​according to the distance weighting rule. When the real-time focal plane temperature falls in interval 1, the weights are w1 = (N-1) / N and w2 = 1 / N; when the real-time focal plane temperature falls in interval 2, the weights are w1 = (N-2) / N and w2 = 2 / N; when the real-time focal plane temperature falls in interval 3, the weights are w1 = (N-3) / N and w2 = 3 / N; and so on. When the real-time focal plane temperature falls in interval N, the weights are w1 = 1 / N and w2 = (N-1) / N. The weighted background calculation formula for step S4 is shown in equation (1.3). Then, two-point correction can be performed to complete the non-uniformity correction. B = Bn-1*W1 + Bn*W2 (1.3).

2. A temperature-corrected infrared baffleless system, characterized in that, The system includes the following modules: Module M1: Employs a multi-segment, multi-background data acquisition system without baffle plates; Module M2: Employs single-frame averaging and multi-frame smoothing to acquire focal plane temperature; Module M3: Calculates weighting coefficients using a weighting system based on mean and distance; Module M4: Calculates weights, performs two-point correction, and completes non-uniformity correction; Module M1 includes the following modules: Module M1.1: Configures the gain of the uncooled detector to three levels: low temperature, normal temperature, and high temperature. Module M1.2: Sets the ambient temperature to -40℃ to +60℃, with three settings. Module M1.3: Collects N1, N2, and N3 background data within three temperature ranges. After setting the temperature in the high and low temperature chamber and maintaining the temperature for a period of time, the detector is covered with a uniform baffle for data acquisition. N1, N2, and N3 correspond to the N background data collected in the low temperature, normal temperature, and high temperature ranges, respectively. Module M2 includes the following modules: Module M2.1: Sum the values ​​of the focal plane temperature points within a single frame, and then divide by the total number of focal plane temperature points; Module M2.2: Multi-frame smoothing is implemented through a system that iteratively calculates the average. The module M3 divides the focal plane temperature of a certain interval into N equal parts, calculates the weighted values, and then designs the weighted values ​​according to the distance weighting rule. When the real-time focal plane temperature falls in interval 1, the weights are w1 = (N-1) / N and w2 = 1 / N; when the real-time focal plane temperature falls in interval 2, the weights are w1 = (N-2) / N and w2 = 2 / N; when the real-time focal plane temperature falls in interval 3, the weights are w1 = (N-3) / N and w2 = 3 / N; and so on. When the real-time focal plane temperature falls in interval N, the weights are w1 = 1 / N and w2 = (N-1) / N. The formula for calculating the weighted background of module M4 is shown in equation (1.3). Then, two-point correction can be performed to complete the non-uniformity correction. B = Bn-1*W1 + Bn*W2 (1.3).

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