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The dynamic range of infrared imaging system is one of the important parameters representing its measurement capability. Extending the dynamic range of infrared imaging system can effectively improve its measurement capability for complex scenes, rapidly changing targets, and more. To improve the dynamic range, firstly, the corresponding relationship between the integration time and dynamic range of infrared imaging system was obtained through radiation calibration experiments, and a non-uniform correction method that adapted to dynamic integration time was proposed. On the basis, a large dynamic range algorithm for infrared imaging systems based on multiple integration times was proposed and the algorithm flowchart was provided. For the same scene, this method utilizes different integration times to collect multiple frames of images and perform image fusion and radiometric calibration parameter fusion, which not only obtains high dynamic range of images but also ensures radiometric measurement accuracy. Lastly, using different temperature blackbodies to construct multi-target complex scenes in the laboratory, and multiple sets of blackbody target images were obtained using an infrared camera and measurement error analysis was conducted, and through processing, high dynamic range images were obtained, the algorithm's effectiveness was verified. The experimental results showed that the algorithm can effectively improve the dynamic range of infrared imaging system, with radiation measurement errors less than 1.5%, at the same time, the high dynamic range images contain more detailed information compared to the unprocessed infrared images, which is more conducive to target detection and recognition, and can meet the measurement application of infrared target characteristics. With the improvement of the frame rate of infrared imaging system, the method can be applied to various research applications such as combustion process analysis, aerodynamic heating analysis, etc.
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