Abstract
Haze often limits visibility and reduces contrast in outdoor images. The degradation varies spatially since it depends on the objects' distances from the camera. This dependency is expressed in the transmission coefficients, which control the attenuation. Restoring the scene radiance from a single image is a highly ill-posed problem, and thus requires using an image prior. Contrary to methods that use patch-based image priors, we propose an algorithm based on a non-local prior. The algorithm relies on the assumption that colors of a haze-free image are well approximated by a few hundred distinct colors, which form tight clusters in RGB space. Our key observation is that pixels in a given cluster are often non-local, i.e., spread over the entire image plane and located at different distances from the camera. In the presence of haze these varying distances translate to different transmission coefficients. Therefore, each color cluster in the clear image becomes a line in RGB space, that we term a haze-line. Using these haze-lines, our algorithm recovers the atmospheric light, the distance map and the haze-free image. The algorithm has linear complexity, requires no training, and performs well on a wide variety of images compared to other state-of-the-art methods.
Original language | English |
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Article number | 8540862 |
Pages (from-to) | 720-734 |
Number of pages | 15 |
Journal | IEEE Transactions on Pattern Analysis and Machine Intelligence |
Volume | 42 |
Issue number | 3 |
DOIs | |
State | Published - 1 Mar 2020 |
Bibliographical note
Funding Information:TT was supported by the The Leona M. and Harry B. Helmsley Charitable Trust and The Maurice Hatter Foundation. Part of this research was supported by ISF grant 1917/ 2015. DB was supported by Apple Graduate Fellowship.
Publisher Copyright:
© 1979-2012 IEEE.
Keywords
- Single image dehazing
- haze removal
ASJC Scopus subject areas
- Software
- Computer Vision and Pattern Recognition
- Computational Theory and Mathematics
- Artificial Intelligence
- Applied Mathematics