Detail enhancement for infrared image based on iterative least squares and difference of Gaussian filter

Zhiqiang Chen; Zehao Zhao; Lei Gaun; Feng Zhou; Yaohong Chen

doi:10.1117/12.2688130

6 November 2023 Detail enhancement for infrared image based on iterative least squares and difference of Gaussian filter

Zhiqiang Chen, Zehao Zhao, Lei Gaun, Feng Zhou, Yaohong Chen

Author Affiliations +

Proceedings Volume 12921, Third International Computing Imaging Conference (CITA 2023); 1292111 (2023) https://doi.org/10.1117/12.2688130
Event: Third International Computing Imaging Conference (CITA 2023), 2023, Sydney, Australia

Abstract

Effective visualization of infrared images with low contrast and low signal-to-noise ratio is one of the key technologies for high-performance infrared imaging systems. The conventional decomposition-based algorithms have advantages in image details enhancement, but still suffer from high computational cost, unbalanced noise suppression and detail information. In this paper, we decompose the base and detail components of the image by the iterative least squares and the difference of Gaussian filter, and further enhance the base layer and the detail layer via plateau equalization and gradient mask, respectively. We then fusion the enhancement result and re-project to eight-bit dynamic range. Experimental results shown that the proposed method achieves a good balance between detail enhancement and computational cost, with a high-performance in different scenes.

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Zhiqiang Chen, Zehao Zhao, Lei Gaun, Feng Zhou, and Yaohong Chen "Detail enhancement for infrared image based on iterative least squares and difference of Gaussian filter", Proc. SPIE 12921, Third International Computing Imaging Conference (CITA 2023), 1292111 (6 November 2023); https://doi.org/10.1117/12.2688130

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KEYWORDS

Image enhancement

Image filtering

Infrared imaging

Image processing

Gaussian filters

Infrared radiation

Optical filters

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