Volume 13 Issue 5
Sep.  2020
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LV Bao-lin, TONG Shou-feng, XU Wei, FENG Qin-ping, WANG De-jiang. Non-uniformity correction of airborne infrared detection system based on inter-frame registration[J]. Chinese Optics, 2020, 13(5): 1124-1137. doi: 10.37188/CO.2020-0109
Citation: LV Bao-lin, TONG Shou-feng, XU Wei, FENG Qin-ping, WANG De-jiang. Non-uniformity correction of airborne infrared detection system based on inter-frame registration[J]. Chinese Optics, 2020, 13(5): 1124-1137. doi: 10.37188/CO.2020-0109

Non-uniformity correction of airborne infrared detection system based on inter-frame registration

doi: 10.37188/CO.2020-0109
Funds:  Supported by National Natural Science Foundation of China (No. 61675202)
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  • During flight, changes in environmental parameters affect the accuracy of non-uniformity correction of airborne infrared point-target detection systems to some extent. Therefore, it is necessary to perform on-board scene-based non-uniformity correction. In this paper, we propose an algorithm based on inter-frame registration to achieve on-board non-uniformity correction. It first preprocesses the images to filter out dead pixels, then calculates a cross-power spectrum with two adjacent frames and determines their registration displacement according to a correlation function that is calculated from the cross-power spectrum. After registering an image, corrective parameters are updated by minimizing the error through a function. The corrective parameters are finally obtained after the above calculations are performed. In an experimental comparison, we simulate a set of non-uniform scene image sequences as the experimental image sequence. This experiment first identified the influence of changes between frames (including displacement, rotation and scaling) on the accuracy of non-uniformity correction. It then used two representative algorithms and the proposed algorithm to process the image series, and compared the performance of the algorithms from the perspective of image quality and convergence speed. The results show that the proposed algorithm has better non-uniformity corrective performance compared with the two other methods. The PSNR increased by over 20 dB, and the SSIM exceeded 0.99. The proposed algorithm has higher complexity, but its convergence speed is much faster, and it is easy to be implemented on hardware platforms, which gives the algorithm possible applications in engineering.

     

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