A novel infrared image enhancement algorithm based on atmospheric transmission model

Xingyou Liu

doi:10.1117/12.2582494

10 November 2020 A novel infrared image enhancement algorithm based on atmospheric transmission model

Xingyou Liu

Proceedings Volume 11584, 2020 International Conference on Image, Video Processing and Artificial Intelligence; 115840X (2020) https://doi.org/10.1117/12.2582494
Event: Third International Conference on Image, Video Processing and Artificial Intelligence, 2020, Shanghai, China

Abstract

In this paper, an infrared image enhancement algorithm based on atmospheric transmission is proposed. First, the algorithm estimates atmospheric light based on a priori principles, that is, the pixel area representing infrared atmospheric light is generally in the upper part of the image and its local contrast is low and its brightness is high. Then, the algorithm estimates the transmittance of the image based on the principle of maximum local contrast of the image, and it uses a guided filtering algorithm to optimize the transmittance. According to the physical model of infrared attenuation in the atmosphere, the infrared image before attenuation is restored. At the same time, this paper uses guided filtering to decompose the image into a basic sub-figure and a detail sub-figure. Among them, the SVD decomposition method is used to improve the brightness of the basic sub-figure. Then, the detail sub-figure and the basic sub-figure are processed by the wavelet transform method, and finally the enhanced infrared image is obtained. Experimental results show that the algorithm in this paper can effectively enhance the infrared image, and the enhancement effect is better than that of ordinary HE, CLAHE, Retinex and other algorithms.

Citation Download Citation

Xingyou Liu "A novel infrared image enhancement algorithm based on atmospheric transmission model", Proc. SPIE 11584, 2020 International Conference on Image, Video Processing and Artificial Intelligence, 115840X (10 November 2020); https://doi.org/10.1117/12.2582494

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