PROCEEDINGS ARTICLE | March 4, 2015
Proc. SPIE. 9443, Sixth International Conference on Graphic and Image Processing (ICGIP 2014)
KEYWORDS: Image fusion, Air contamination, Image processing, Digital filtering, Image restoration, Gaussian filters, Image transmission, Image enhancement, Atmospheric modeling, Model-based design
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..
