Panoramic real-time scene correction method and system based on infrared line detector

Abstract

The invention provides a panoramic real-time scene correction method and system based on an infrared line detector, and the method comprises the steps: carrying out the uniform partitioning of an image, and guaranteeing the non-uniformity of a current scene to the maximum degree; a uniform scene meeting conditions is automatically selected by using a multi-column accumulation technology to perform non-uniformity correction, so that the problem of overall non-uniformity caused by large gray dynamic range difference of scenes at different angles is solved, meanwhile, the influence of a high-temperature target and a low-temperature target is eliminated, and the function of improving the uniformity of panoramic imaging is realized. Through engineering verification, manual intervention is not needed in the panoramic imaging process, automatic real-time scene correction is achieved, panoramic imaging is continuous and uninterrupted, the image uniformity is not reduced in the long-time continuous working process, and the method can be widely applied to a monitoring system.

Description

Technical Field

[0001] This invention belongs to the field of infrared imaging technology, specifically relating to a panoramic real-time scene correction method and system based on an infrared linear array detector. Background Technology

[0002] Infrared linear array detectors have a simple structure and can achieve high resolution by outputting one-dimensional images. When combined with a 360° rotating turntable, infrared linear array detectors can output two-dimensional panoramic images.

[0003] Long-wave infrared detectors are limited by the influence of mercury cadmium telluride infrared materials, resulting in poor non-uniformity. Correction imaging effects for general blackbody calibration are generally poor, manifesting as decreased image uniformity and the appearance of horizontal stripes when there are significant temperature variations in the scene. After prolonged operation, heat generation in the optical system or thermal radiation from the detector itself can also affect image uniformity. Summary of the Invention

[0004] The technical problem to be solved by the present invention is to provide a panoramic real-time scene correction method and system based on infrared linear detectors to improve the uniformity of panoramic imaging.

[0005] The technical solution adopted by this invention to solve the above-mentioned technical problems is as follows: a panoramic real-time scene correction method based on an infrared linear detector, comprising the following steps: S1: Acquire panoramic images and perform initial multi-point column non-uniformity correction on the images by limiting the field of view and introducing a reference benchmark; S2: Divide the panoramic image after the initial correction into evenly spaced blocks according to angles; S3: Calculate the mean of the segmented image, and calculate the upper and lower limits of the corrected grayscale based on the input threshold; S4: Create space to store the corresponding B table based on the number of image blocks; S5: When the data in each column of the segmented image is within the range of the upper and lower limits of the corrected grayscale, the column data are summed and averaged to obtain the scene grayscale value and stored in the corresponding B table. S6: Select the closest K-table data based on the scene grayscale value; the K-table stores the pixel average value under pre-calibrated temperature limiting conditions; S7: Perform non-uniformity correction on the segmented image according to the K table, and output the scene-corrected image.

[0006] According to the above scheme, in step S1, Indicates the current pixel position in the panoramic image. This is the raw data of the current pixel in the panoramic image. This is the average value of all consecutive data points in the current pixel multi-point column of the panoramic image. The overall image mean of all columns of image regions at the center of the baffle, used to limit the field of view and introduce a reference benchmark, is the current pixel-corrected data. for: .

[0007] According to the above scheme, in step S3, the mean value of the corrected image of the segmented image is calculated. The input threshold is Then correct the upper limit of grayscale. for: , Correcting the lower limit of grayscale for: .

[0008] According to the above scheme, in step S6, Indicates the current pixel position. This represents the mean of all original pixel data for high temperature. This represents the mean of all original pixel data at low temperature. This represents the mean of the original data for the current pixel at high temperature. This represents the mean of the original data for the current pixel at low temperature. The K-table data corresponding to the current pixel is as follows: .

[0009] According to the above scheme, the specific steps in step S6 are as follows: Before the entire process begins, a blackbody is selected, and K-table data corresponding to different temperatures and average values ​​are stored according to the blackbody calibration method.

[0010] According to the above scheme, in step S7, Indicates the current pixel position. Indicates the current image block. This represents the K-table data corresponding to the pixels in the current block. This represents the raw data of the pixel corresponding to the current block. This represents the B-table data updated in real time during the acquisition of each panoramic image in step S5, and the data after current block correction. for: .

[0011] According to the above scheme, the B table of the Nth image is calculated in real time during the imaging process of the Nth image; when the (N+1)th image is imaged, the B table of the Nth image is updated.

[0012] According to the above scheme, during the scene correction process of each image, a uniform scene that meets the conditions of step S5 is automatically selected for cumulative calculation.

[0013] A panoramic real-time scene correction system, characterized in that: It includes an infrared array detector, a baffle, a processing unit, temporary storage space, and main storage space; Infrared array detectors are used to acquire panoramic images; The baffle is used to limit the field of view and introduce a reference point; The processing unit is used for image processing and calculation; Temporary storage space is used to store table B and temporarily store table K; The main storage space is used to store table K.

[0014] A computer memory storing a computer program executable by a computer processor, the computer program performing a panoramic real-time scene correction method based on an infrared linear detector.

[0015] The beneficial effects of this invention are as follows: 1. The present invention provides a panoramic real-time scene correction method and system based on an infrared linear detector. By uniformly dividing the image into blocks, the non-uniformity of the current scene is maximized. By using multi-column accumulation technology to automatically select uniform scenes that meet the conditions for non-uniformity correction, the overall non-uniformity problem caused by large differences in the dynamic range of grayscale of scenes at different angles is solved. At the same time, the influence of high-temperature targets and low-temperature targets is eliminated, thereby realizing the function of improving the uniformity of panoramic imaging.

[0016] 2. Through engineering verification, the present invention works stably in the panoramic imaging process without manual intervention, realizes automatic real-time scene correction, and ensures continuous panoramic imaging without interruption. The image uniformity does not decrease during long-term continuous operation, and it can be widely used in monitoring systems.

[0017] Of course, any product implementing this invention does not necessarily need to achieve all of the advantages described above at the same time. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 This is a flowchart of an embodiment of the present invention.

[0020] Figure 2 This is a schematic diagram of panoramic correction imaging according to an embodiment of the present invention. Detailed Implementation

[0021] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0022] Example 1 See Figure 1 The specific steps of a panoramic real-time scene correction method based on infrared linear detectors are as follows: S1: The infrared array detector is powered on to acquire a 360° panoramic image and performs the first multi-point array non-uniformity correction through the baffle. This correction operation is performed only once and is used to provide initial correction parameters for subsequent scene corrections; let... Indicates the current pixel position. This is the raw data for the current pixel. It is the average of 64 consecutive data points in the current pixel multi-point column. The average value of the entire image area of ​​the 64 columns in the center of the baffle, after current pixel correction. for: ; S2: The 360° panoramic image is evenly divided into blocks to maximize the non-uniformity of the current scene, thereby solving the overall non-uniformity problem caused by the large difference in the dynamic range of grayscale in different angle scenes. S3: Calculate the corrected image mean for each image block. Based on the input threshold Calculate the upper and lower limits of the corrected grayscale; The upper and lower limits of the corrected grayscale are used in subsequent steps to distinguish between high-temperature and low-temperature targets that affect non-uniformity correction; let... Indicates the upper limit of grayscale correction. This indicates the lower limit of grayscale correction. The formulas for the upper and lower limits of grayscale correction are as follows: , ; S4: Allocate the corresponding block B tablespace in the temporary storage space according to the number of image blocks; S5: When the data in each column of the segmented image is within the range of the upper and lower limits of the corrected gray level, the column data are summed, averaged, and stored in the corresponding B table; Since each image corresponds to a large imaging angle, updating the B table by accumulating and averaging the data helps to improve the non-uniformity of panoramic imaging. S6: Read the data from table K from the main storage space to the temporary storage space, and select the closest table K based on the scene grayscale value; set up Indicates the current pixel position. This represents the mean of all original pixel data for high temperature. This represents the mean of all original pixel data at low temperature. This represents the mean of the original data for the current pixel at high temperature. The K-table for the current pixel represents the mean of the original data at low temperature. The formula for calculating the K-table for the current pixel is: ; Before the entire process begins, a blackbody needs to be selected in advance, and the K table corresponding to different temperatures and average values ​​needs to be stored in the main storage space according to the blackbody calibration method. S7: Perform non-uniformity correction on the segmented image and output the scene-corrected image; Indicates the current pixel position. Indicates the current image block. The K table represents the pixels corresponding to the current block. This represents the raw data of the pixel corresponding to the current block. This represents Table B, which is calculated and updated in real time for each panoramic image in step S5, and contains the data after the current block correction. for: ; During the imaging process of the Nth image, the B table of the Nth image is calculated in real time; when the (N+1)th image is imaged, the B table of the Nth image is updated; during the scene correction process of each image, a uniform scene that meets the conditions of step S5 is automatically selected for cumulative calculation.

[0023] This embodiment maximizes the non-uniformity of the current scene by uniformly dividing the image into blocks; it automatically selects uniform scenes that meet the conditions for non-uniformity correction using multi-column accumulation technology, which solves the overall non-uniformity problem caused by large differences in the dynamic range of grayscale in scenes from different angles, while eliminating the influence of high-temperature and low-temperature targets, thus realizing the function of improving the uniformity of panoramic imaging.

[0024] Example 2 The steps in this embodiment are the same as in Embodiment 1, except that each step is applied to a specific instance. The infrared array detector uses a long-wave infrared array 1024*6 detector with 16-channel output and a 3-level TDI structure; the processing unit uses an XC7K325T FPGA for image processing; the temporary storage space uses two MT41J256M16 DDR3 chips; and the main storage space uses an MT25QL01G FLASH. Specifically, the following steps are included: S1: Power-on calibration; The infrared array detector is powered on, and the first multi-point array calibration is performed using the baffle. S2: Panoramic Segmentation; uniformly divides the 360° panoramic image into blocks; The infrared array detector operates at a main clock of 4MHz, with an output column period of 17.75μs, a focal length of 200mm, and a turntable rotation speed of 290.51° / s. The total number of infrared output columns in one revolution is approximately 69,813. The panoramic image is divided into 8 blocks, each corresponding to a 45° area, with approximately 8,727 columns in each block. S3: Block scene correction; calculate the mean value of each image block and correct the upper and lower limits of grayscale; Based on the response of the 1024*6 long-wave infrared array detector, the dynamic range of the 14-bit AD is [0-16383]. The threshold range of the upper and lower limits of grayscale is set to 700 to exclude high-temperature and low-temperature targets in the statistical scenario. S4: DDR block processing; an independent correction B table is allocated in DDR according to the number of blocks; the size of each B table is 1024*16 bits; S5: Block B-table calculation; perform cumulative averaging calculation on the column data of the block image of the panoramic imaging of the infrared column detector that meets the upper and lower limits of grayscale, and store the result in the corresponding B-table position in DDR. S6: Adjust the K-table; automatically select the K-table based on the mean of the segmented image; Before the entire process begins, a blackbody needs to be selected in advance, and K tables corresponding to different temperatures and average values ​​need to be stored according to the blackbody calibration method. According to the usage mode of the infrared array detector, the integration time is fixed at 17μs and the gain is 1.62. The blackbody temperature is raised from -30℃ to 70℃, and K tables corresponding to the interval temperature points are calculated at 15℃ intervals. All K tables are stored in the main storage space. S7: Scene Correction; Performs non-uniformity correction on the segmented image and outputs a scene-corrected image.

[0025] This embodiment has been verified through engineering practice. It works stably during panoramic imaging without the need for manual intervention, achieves automatic real-time scene correction, and ensures continuous panoramic imaging without interruption. The image uniformity does not decrease during long-term continuous operation, and it can be widely used in monitoring systems.

[0026] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0027] Example 3 This embodiment is used to implement the principle of the above method embodiment to construct a panoramic real-time scene correction system based on an infrared linear detector, including an infrared linear detector, a baffle, a processing unit, a temporary storage space and a main storage space.

[0028] The infrared array detector uses a long-wave infrared array 1024*6 detector with 16-channel output and a 3-level TDI structure, and is used to acquire panoramic images. The baffle is used to limit the field of view and introduce a reference point; The processing unit uses an XC7K325T FPGA for image processing, which is used for image processing and calculation. The temporary storage space uses two MT41J256M16 DDR3 chips to store table B and temporarily store table K. The main storage space uses FLASH model MT25QL01G to store the K table.

[0029] It should be noted that, depending on the implementation needs, the various steps / components described in this application can be broken down into more steps / components, or two or more steps / components or parts of the operation of steps / components can be combined into new steps / components to achieve the purpose of this invention.

[0030] This embodiment also includes a processor, a communication interface, a memory, and a communication bus; wherein the processor, the communication interface, and the memory communicate with each other through the communication bus; the memory stores a computer program, and when the program is executed by the processor, the processor performs the steps of a panoramic real-time scene correction method based on an infrared linear detector.

[0031] This embodiment also provides a computer-readable storage medium storing executable instructions that, when executed by a processor, enable the processor to implement a panoramic real-time scene correction method based on an infrared linear detector.

[0032] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects.

[0033] Furthermore, this application may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0034] This application is described with reference to the flowchart of the method and computer program product according to Embodiment 1 and the block diagram of the device (system) according to Embodiment 3. It should be understood that each step or block in the flowchart or block diagram, as well as combinations of steps or blocks in the flowchart or block diagram, can be implemented by computer program instructions.

[0035] These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing device to produce a machine, such that the instructions, which are executable by the processor of the computer or other programmable data processing device, produce instructions for implementing the process. Figure 1 One or more processes or boxes Figure 1 A panoramic real-time scene correction system based on an infrared linear array detector, which specifies the functions in one or more boxes.

[0036] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes or boxes Figure 1 The function specified in one or more boxes.

[0037] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes or boxes Figure 1 The steps of a panoramic real-time scene correction method based on an infrared linear detector are specified in one or more boxes.

[0038] The above embodiments are only used to illustrate the design concept and features of the present invention, and their purpose is to enable those skilled in the art to understand the content of the present invention and implement it accordingly. The protection scope of the present invention is not limited to the above embodiments. Therefore, all equivalent changes or modifications made based on the principles and design ideas disclosed in the present invention are within the protection scope of the present invention.

Claims

1. A panoramic real-time scene correction method based on an infrared linear detector, characterized in that: Includes the following steps: S1: Acquire panoramic images and perform initial multi-point column non-uniformity correction on the images by limiting the field of view and introducing a reference benchmark; S2: Divide the panoramic image after the initial correction into evenly spaced blocks according to angles; S3: Calculate the mean of the segmented image, and calculate the upper and lower limits of the corrected grayscale based on the input threshold; S4: Create space to store the corresponding B table based on the number of image blocks; S5: When the data in each column of the segmented image is within the range of the upper and lower limits of the corrected grayscale, the column data are summed and averaged to obtain the scene grayscale value and stored in the corresponding B table. S6: Select the closest K-table data based on the scene grayscale value; the K-table stores the pixel average value under pre-calibrated temperature limiting conditions; S7: Perform non-uniformity correction on the segmented image according to the K table, and output the scene-corrected image.

2. The panoramic real-time scene correction method based on an infrared linear detector according to claim 1, characterized in that: In step S1, Indicates the current pixel position in the panoramic image. This is the raw data of the current pixel in the panoramic image. This is the average value of all consecutive data points in the current pixel multi-point column of the panoramic image. The overall image mean of all columns of image regions at the center of the baffle, used to limit the field of view and introduce a reference benchmark, is the current pixel-corrected data. for: 。 3. The panoramic real-time scene correction method based on an infrared linear detector according to claim 1, characterized in that: In step S3, the mean value of the corrected image of the segmented image is calculated. The input threshold is Then correct the upper limit of grayscale. for: ， Correcting the lower limit of grayscale for: 。 4. The panoramic real-time scene correction method based on an infrared linear detector according to claim 1, characterized in that: In step S6, Indicates the current pixel position. This represents the mean of all original pixel data for high temperature. This represents the mean of all original pixel data at low temperature. This represents the mean of the original data for the current pixel at high temperature. This represents the mean of the original data for the current pixel at low temperature. The K-table data corresponding to the current pixel is as follows: 。 5. A panoramic real-time scene correction method based on an infrared linear detector according to claim 1, characterized in that: The specific steps in step S6 are as follows: Before the entire process begins, a blackbody is selected, and K-table data corresponding to different temperatures and average values ​​are stored according to the blackbody calibration method.

6. The panoramic real-time scene correction method based on an infrared linear detector according to claim 1, characterized in that: In step S7, Indicates the current pixel position. Indicates the current image block. This represents the K-table data corresponding to the pixels in the current block. This represents the raw data of the pixel corresponding to the current block. This represents the B-table data updated in real time during the acquisition of each panoramic image in step S5, and the data after current block correction. for: 。 7. The panoramic real-time scene correction method based on an infrared linear detector according to claim 1, characterized in that: The B table for the Nth image is calculated in real time during the imaging process of the Nth image; when the (N+1)th image is imaged, the B table for the Nth image is updated.

8. A panoramic real-time scene correction method based on an infrared linear detector according to claim 1, characterized in that: During the scene correction process for each image, uniform scenes that meet the conditions in step S5 are automatically selected for cumulative calculation.

9. A panoramic real-time scene correction system for the panoramic real-time scene correction method based on infrared linear detectors as described in any one of claims 1 to 8, characterized in that: It includes an infrared array detector, a baffle, a processing unit, temporary storage space, and main storage space; Infrared array detectors are used to acquire panoramic images; The baffle is used to limit the field of view and introduce a reference point; The processing unit is used for image processing and calculation; Temporary storage space is used to store table B and temporarily store table K; The main storage space is used to store table K.

10. A computer memory, characterized in that: It contains a computer program that can be executed by a computer processor, which performs a panoramic real-time scene correction method based on an infrared linear detector as described in any one of claims 1 to 8.

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