Contrast restoration of weather degraded images
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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…
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Topics
Keywords
- Haze
- Artificial intelligence
- Computer science
- Computer vision
- Contrast (vision)
- A priori and a posteriori
- Classification of discontinuities
- Remote sensing
UN Sustainable Development Goals
- Sustainable cities and communities
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