Efficient Belief Propagation for Early Vision
International Journal of Computer Vision
ACM SIGGRAPH 2008 papers
Deep photo: model-based photograph enhancement and viewing
ACM SIGGRAPH Asia 2008 papers
A fast semi-inverse approach to detect and remove the haze from a single image
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part II
Contrast restoration of weather degraded images
IEEE Transactions on Pattern Analysis and Machine Intelligence
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We present a novel strategy to restore outdoor images degraded by the atmospheric phenomena such as haze or fog. Since both the depth map of the scene and the airlight constant are unknown, this problem is mathematically ill-posed. Firstly, we present a straightforward approach that is able to estimate accurately the airlight constant by searching the regions with the highest intensity. Afterwards, based on a graphical Markov random field (MRF) model, we introduce a robust optimization framework that is able to transport the local minima over large neighborhoods while smoothing the transmission map but also preserving the important depth discontinuities of the estimated depth. The method has been tested extensively for real outdoor images degraded by haze or fog. The comparative results with the existing state-of-the-art techniques demonstrate the advantage of our approach.