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15 October 2015 Locally adaptive regression filter-based infrared focal plane array non-uniformity correction
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Proceedings Volume 9674, AOPC 2015: Optical and Optoelectronic Sensing and Imaging Technology; 967431 (2015) https://doi.org/10.1117/12.2202933
Event: Applied Optics and Photonics China (AOPC2015), 2015, Beijing, China
Abstract
Due to the limitations of the manufacturing technology, the response rates to the same infrared radiation intensity in each infrared detector unit are not identical. As a result, the non-uniformity of infrared focal plane array, also known as fixed pattern noise (FPN), is generated. To solve this problem, correcting the non-uniformity in infrared image is a promising approach, and many non-uniformity correction (NUC) methods have been proposed. However, they have some defects such as slow convergence, ghosting and scene degradation. To overcome these defects, a novel non-uniformity correction method based on locally adaptive regression filter is proposed. First, locally adaptive regression method is used to separate the infrared image into base layer containing main scene information and the detail layer containing detailed scene with FPN. Then, the detail layer sequence is filtered by non-linear temporal filter to obtain the non-uniformity. Finally, the high quality infrared image is obtained by subtracting non-uniformity component from original image. The experimental results show that the proposed method can significantly eliminate the ghosting and the scene degradation. The results of correction are superior to the THPF-NUC and NN-NUC in the aspects of subjective visual and objective evaluation index.
© (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jia Li, Hanlin Qin, Xiang Yan, He Huang, Yingjuan Zhao, and Huixin Zhou "Locally adaptive regression filter-based infrared focal plane array non-uniformity correction", Proc. SPIE 9674, AOPC 2015: Optical and Optoelectronic Sensing and Imaging Technology, 967431 (15 October 2015); https://doi.org/10.1117/12.2202933
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