A multi-scale fusion-based dark channel prior dehazing algorithm

Yujun Zeng; Xiaolin Liu

doi:10.1117/12.2179586

4 March 2015 A multi-scale fusion-based dark channel prior dehazing algorithm

Yujun Zeng, Xiaolin Liu

Proceedings Volume 9443, Sixth International Conference on Graphic and Image Processing (ICGIP 2014); 94431C (2015) https://doi.org/10.1117/12.2179586
Event: Sixth International Conference on Graphic and Image Processing (ICGIP 2014), 2014, Beijing, China

Abstract

During model-based image dehazing, the role of the accuracy of transmission estimation is crucial, which has a decisive effect on the final result. Considering that an ideal transmission map must be smooth, edge-preserving and free of redundant false details, a fusion-based dark channel prior (DCP) dehazing algorithm is presented in this paper. On the basis of DCP, a pixel-wise and a patch-wise transmission maps are obtained. Then an L0 smoothing filter and a large scale Gaussian filter are applied to them respectively. Finally, a much more accurate refined transmission map is attained through fusion and a haze-free image is restored using the atmosphere degradation model. Furthermore, a novel scheme for setting the lower bound of transmission adaptively is also put forward. Experiments demonstrate a better and faster dehazing capability over original DCP algorithm and state-of-the-art dehazing methods, especially in suppressing halo artifacts, restoring details and coping with the haze existing in small-scale areas of depth discontinuity occluded by foreground..

Citation Download Citation

Yujun Zeng and Xiaolin Liu "A multi-scale fusion-based dark channel prior dehazing algorithm", Proc. SPIE 9443, Sixth International Conference on Graphic and Image Processing (ICGIP 2014), 94431C (4 March 2015); https://doi.org/10.1117/12.2179586

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KEYWORDS

Air contamination

Image fusion

Image transmission

Atmospheric modeling

Gaussian filters

Image processing

Model-based design

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