Paper
1 November 2016 A curvature filter and PDE based non-uniformity correction algorithm
Author Affiliations +
Proceedings Volume 10157, Infrared Technology and Applications, and Robot Sensing and Advanced Control; 1015736 (2016) https://doi.org/10.1117/12.2247324
Event: International Symposium on Optoelectronic Technology and Application 2016, 2016, Beijing, China
Abstract
In this paper, a curvature filter and PDE based non-uniformity correction algorithm is proposed, the key point of this algorithm is the way to estimate FPN. We use anisotropic diffusion to smooth noise and Gaussian curvature filter to extract the details of original image. Then combine these two parts together by guided image filter and subtract the result from original image to get the crude approximation of FPN. After that, a Temporal Low Pass Filter (TLPF) is utilized to filter out random noise and get the accurate FPN. Finally, subtract the FPN from original image to achieve non-uniformity correction. The performance of this algorithm is tested with two infrared image sequences, and the experimental results show that the proposed method achieves a better non-uniformity correction performance.
© (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Kuanhong Cheng, Huixin Zhou, Hanlin Qin, Dong Zhao, Kun Qian, Shenghui Rong, and Shimin Yin "A curvature filter and PDE based non-uniformity correction algorithm", Proc. SPIE 10157, Infrared Technology and Applications, and Robot Sensing and Advanced Control, 1015736 (1 November 2016); https://doi.org/10.1117/12.2247324
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KEYWORDS
Image filtering

Nonuniformity corrections

Partial differential equations

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