DocumentCode :
1211244
Title :
Contrast restoration of weather degraded images
Author :
Narasimhan, Srinivasa G. ; Nayar, Shree K.
Author_Institution :
Dept. of Comput. Sci., Columbia Univ., New York, NY, USA
Volume :
25
Issue :
6
fYear :
2003
fDate :
6/1/2003 12:00:00 AM
Firstpage :
713
Lastpage :
724
Abstract :
Images of outdoor scenes captured in bad weather suffer from poor contrast. Under bad weather conditions, the light reaching a camera is severely scattered by the atmosphere. The resulting decay in contrast varies across the scene and is exponential in the depths of scene points. Therefore, traditional space invariant image processing techniques are not sufficient to remove weather effects from images. We present a physics-based model that describes the appearances of scenes in uniform bad weather conditions. Changes in intensities of scene points under different weather conditions provide simple constraints to detect depth discontinuities in the scene and also to compute scene structure. Then, a fast algorithm to restore scene contrast is presented. In contrast to previous techniques, our weather removal algorithm does not require any a priori scene structure, distributions of scene reflectances, or detailed knowledge about the particular weather condition. All the methods described in this paper are effective under a wide range of weather conditions including haze, mist, fog, and conditions arising due to other aerosols. Further, our methods can be applied to gray scale, RGB color, multispectral and even IR images. We also extend our techniques to restore contrast of scenes with moving objects, captured using a video camera.
Keywords :
computer vision; image colour analysis; image restoration; video cameras; IR images; RGB color images; camera; fog; gray scale images; haze; image contrast restoration; mist; moving objects; multispectral images; outdoor scenes; physics-based model; scene contrast restoration; scene reconstruction; scene structure; space invariant image processing; video camera; weather degraded images; Atmosphere; Atmospheric modeling; Cameras; Degradation; Image restoration; Layout; Light scattering; Optical polarization; Optical scattering; Painting;
fLanguage :
English
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publisher :
ieee
ISSN :
0162-8828
Type :
jour
DOI :
10.1109/TPAMI.2003.1201821
Filename :
1201821
Link To Document :
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