Paper
26 October 2013 A unified dehazing approach for infrared images
Tao Fang, Zhiguo Cao, Ruicheng Yan
Author Affiliations +
Proceedings Volume 8917, MIPPR 2013: Multispectral Image Acquisition, Processing, and Analysis; 89170V (2013) https://doi.org/10.1117/12.2031255
Event: Eighth International Symposium on Multispectral Image Processing and Pattern Recognition, 2013, Wuhan, China
Abstract
Images are usually degraded by haze and fog due to atmospheric absorption and scattering. Especially for remote sensing, degraded images which suffer from haze will highly probably lose detailed information. Nowadays researches on haze removal mainly focus on visible images. However, as infrared imaging is more and more widely used in many fields, a comprehensive study of the effects of fog on infrared images is urgent. In this paper, we firstly introduce that the obvious attenuation effects of fog on infrared images by analyzing the mid-infrared images captured under different weather conditions. Therefore, we propose a unified dehazing approach for infrared images. The proposed approach mainly includes three steps. The first step is to obtain the local transmission of the original hazed images by using the statistical prior knowledge known as “dark channel” which is similar to visible images. With local transmission, the refined transmission map is estimated in a soft matting framework. Due to atmospheric scattering model, dehazed infrared images can be recovered finally. From experimental results, it is quantitatively demonstrated that the proposed approach can significantly improve the quality of hazed images by using principle component analysis technique.
© (2013) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Tao Fang, Zhiguo Cao, and Ruicheng Yan "A unified dehazing approach for infrared images", Proc. SPIE 8917, MIPPR 2013: Multispectral Image Acquisition, Processing, and Analysis, 89170V (26 October 2013); https://doi.org/10.1117/12.2031255
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Cited by 2 scholarly publications.
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KEYWORDS
Infrared imaging

Infrared radiation

Atmospheric modeling

Fiber optic gyroscopes

Scattering

Visible radiation

Air contamination

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