Effective dark-corner noise removal for infrared images based on spatial-temporal features

Lizhen Liu; Canbing Zhao; Yulu Su; Wenqing Hong; Qian Li; MingDong Jia; Peng Ge; Haihu Wang

doi:10.1117/12.2605377

24 November 2021 Effective dark-corner noise removal for infrared images based on spatial-temporal features

Lizhen Liu, Canbing Zhao, Yulu Su, Wenqing Hong, Qian Li, MingDong Jia, Peng Ge, Haihu Wang

Proceedings Volume 12065, AOPC 2021: Optical Sensing and Imaging Technology; 120651D (2021) https://doi.org/10.1117/12.2605377
Event: Applied Optics and Photonics China 2021, 2021, Beijing, China

Abstract

Infrared images typically contain obvious dark-corner noise. It is a challenging task to eliminate such noise with the acceptable computation overhead and time overhead. In this paper, we introduce an eﬀective dark-corner noise removal algorithm consists of two consecutive processing procedures. Firstly, in order to eﬀectively ﬁlter dark-corner noise with as few as frames of infrared images, the proposed algorithm accumulates the low-frequency pixels during the several diﬀerent frames of infrared images and eliminates the dark-corner noise by subtracting this parameter from the original infrared image. Then, this algorithm sets several detection windows for dark-corner noise to obtain another additive correction parameter and subtract this parameter from the original infrared image. We demonstrate the eﬀectiveness of our algorithm from experimental perspective.

Citation Download Citation

Lizhen Liu, Canbing Zhao, Yulu Su, Wenqing Hong, Qian Li, MingDong Jia, Peng Ge, and Haihu Wang "Effective dark-corner noise removal for infrared images based on spatial-temporal features", Proc. SPIE 12065, AOPC 2021: Optical Sensing and Imaging Technology, 120651D (24 November 2021); https://doi.org/10.1117/12.2605377

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