Abstract
+ , -./0%12$%& !#3 4. $5& -6 DCP 3 ,78$%&9:; ?@ABC'DEFGHIJBKLMN, IOP:LKOQ IR4. STE ,UVWX$%&3 ,&FGH -KNYZ[6\ 4. ] /0%12$%&^N !_#`>E'(&'a\Kb4. cd`> 3 I$53 De> -&fDEghia Kb #.'(Dk(ia Kb4.AbstractThis paper presents a method of single image dehazing and surface-based feature detection for remote sensing images. In the conventional dark channel prior (DCP) algorithm, the resulting transmission map invariably includes some block artifacts because of patch-based processing. This also causes image blur. Therefore, a refined transmission map based on a hidden Markov random field and expectation-maximization algorithm can reduce the block artifacts and also increase the image clarity. Also, the proposed algorithm enhances the accuracy of image matching surface-based features in an remote sensing image. Experimental results confirm that the proposed algorithm is superior to conventional algorithms in image haze removal. Moreover, the proposed algorithm is suitable for the problem of image matching based on feature extraction.Keyword : Image matching, feature, haze removal
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