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2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'01) - Volume 2
Removing Weather Effects from Monochrome Images
Kauai, Hawaii
December 08-December 14
ISBN: 0-7695-1272-0
Srinivasa G. Narasimhan, Columbia University
Shree K. Nayar, Columbia University
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. In this paper, we present a fast physics-based method to compute scene structure and hence restore contrast of the scene from two or more images taken in bad weather. In contrast to previous techniques, our method does not require any a priori weather-specific or scene information, and is effective under a wide range of weather conditions including haze, mist, fog and other aerosols. Further, our method can be applied to gray-scale, RGB color, multi-spectral and even IR images. We also extend the technique to restore contrast of scenes with moving objects, captured using a video camera.
Citation:
Srinivasa G. Narasimhan, Shree K. Nayar, "Removing Weather Effects from Monochrome Images," cvpr, vol. 2, pp.186, 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'01) - Volume 2, 2001
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