Temporal high-pass non-uniformity correction algorithm based on grayscale mapping and hardware implementation

Minglei Jin; Weiqi Jin; Yiyang Li; Shuo Li

doi:10.1117/12.2191836

5 August 2015 Temporal high-pass non-uniformity correction algorithm based on grayscale mapping and hardware implementation

Minglei Jin, Weiqi Jin, Yiyang Li, Shuo Li

Author Affiliations +

Proceedings Volume 9622, 2015 International Conference on Optical Instruments and Technology: Optoelectronic Imaging and Processing Technology; 962210 (2015) https://doi.org/10.1117/12.2191836
Event: International Conference on Optical Instruments and Technology 2015, 2015, Beijing, China

Abstract

In this paper, we propose a novel scene-based non-uniformity correction algorithm for infrared image processing-temporal high-pass non-uniformity correction algorithm based on grayscale mapping (THP and GM). The main sources of non-uniformity are: (1) detector fabrication inaccuracies; (2) non-linearity and variations in the read-out electronics and (3) optical path effects. The non-uniformity will be reduced by non-uniformity correction (NUC) algorithms. The NUC algorithms are often divided into calibration-based non-uniformity correction (CBNUC) algorithms and scene-based non-uniformity correction (SBNUC) algorithms. As non-uniformity drifts temporally, CBNUC algorithms must be repeated by inserting a uniform radiation source which SBNUC algorithms do not need into the view, so the SBNUC algorithm becomes an essential part of infrared imaging system. The SBNUC algorithms’ poor robustness often leads two defects: artifacts and over-correction, meanwhile due to complicated calculation process and large storage consumption, hardware implementation of the SBNUC algorithms is difficult, especially in Field Programmable Gate Array (FPGA) platform. The THP and GM algorithm proposed in this paper can eliminate the non-uniformity without causing defects. The hardware implementation of the algorithm only based on FPGA has two advantages: (1) low resources consumption, and (2) small hardware delay: less than 20 lines, it can be transplanted to a variety of infrared detectors equipped with FPGA image processing module, it can reduce the stripe non-uniformity and the ripple non-uniformity.

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Minglei Jin, Weiqi Jin, Yiyang Li, and Shuo Li "Temporal high-pass non-uniformity correction algorithm based on grayscale mapping and hardware implementation", Proc. SPIE 9622, 2015 International Conference on Optical Instruments and Technology: Optoelectronic Imaging and Processing Technology, 962210 (5 August 2015); https://doi.org/10.1117/12.2191836

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KEYWORDS

Detection and tracking algorithms

Nonuniformity corrections

Image processing

Field programmable gate arrays

Expectation maximization algorithms

Evolutionary algorithms

Imaging systems

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