5 May 2017 Visibility enhancement of multi-waveband infrared images from degraded visual environment
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Abstract
Multi-waveband infrared (IR) sensors capture more spectral information of atmospheric particles and may provide better penetration thru dust under dynamically changing conditions. Therefore, enhancing the visibility of multi-waveband infrared images obtained in degraded visual environment (DVE) is an important way to improve the perception of the environment under DVE conditions. In this paper, we present a system to enhance visibility in DVE conditions by modifying the wavelet coefficients of multi-waveband IR images. In the proposed system, input multi-waveband IR images are transferred into the wavelet domain using an integer lifting wavelet transformation. The low-frequency wavelet coefficients in each waveband are independently modified by an adaptive histogram equalization technique for improving the contrast of the images. To process high-frequency wavelet coefficients, a joint edge-mapping filter is applied to the multi-waveband high-frequency wavelet coefficients to find an edge map for each subband of wavelet coefficients; then a nonlinear filter is used to remove noise and enhance edge coefficients. Finally, the inverse lifting wavelet transformation is applied to the modified multi-waveband wavelet coefficients to obtain enhanced multiwaveband IR images. We tested the proposed system with degraded multi-waveband IR images obtained from a helicopter landing in brownout conditions. Our experimental results show that the proposed system is effective for enhancing the visibility of multi-waveband IR images under DVE conditions.
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Qin Jiang, Qin Jiang, Yuri Owechko, Yuri Owechko, Brendan Blanton, Brendan Blanton, } "Visibility enhancement of multi-waveband infrared images from degraded visual environment", Proc. SPIE 10197, Degraded Environments: Sensing, Processing, and Display 2017, 101970D (5 May 2017); doi: 10.1117/12.2262600; https://doi.org/10.1117/12.2262600
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