期刊名称：International Journal of Signal Processing, Image Processing and Pattern Recognition
印刷版ISSN：2005-4254
出版年度：2016
卷号：9
期号：2
页码：379-392
DOI：10.14257/ijsip.2016.9.2.32
出版社：SERSC
摘要：At present, greatest outdoor video-surveillance, optical remote sensing systems and driver-assistance have been designed to work under decent visibility weather conditions. Less visibility often happens weather of hazy or foggy conditions and can strongly influence accuracy or even general functionality of such vision systems. Fog reduces the visibility of a scene and thus the performance of numerous algorithms of computer vision which use feature knowledge. Fog formation is the function of the depth. Estimation of depth knowledge is under constraint problem if single image is presented. Hence, fog removal need assumptions or prior information. In this paper, present a novel algorithm for fog or haze removal purpose with combination of edge enhancement method, color enhancement method, adjustable empirical function and also Wiener filter for efficient outcomes.
关键词：fog removal; Wiener filter; edges and color enhancement; Gaussian; etc
