Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
A technical introduction to digital video
A technical introduction to digital video
International Journal of Computer Vision - Special issue on statistical and computational theories of vision: modeling, learning, sampling and computing, Part I
Belief Propagation and Revision in Networks with Loops
Belief Propagation and Revision in Networks with Loops
Bottom reflectance influence on a color correction algorithm for underwater images
SCIA'03 Proceedings of the 13th Scandinavian conference on Image analysis
Visual inspection of sea bottom structures by an autonomousunderwater vehicle
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Underwater image processing: state of the art of restoration and image enhancement methods
EURASIP Journal on Advances in Signal Processing - Special issue on advances in signal processing for maritime applications
Visual enhancement of underwater images using Empirical Mode Decomposition
Expert Systems with Applications: An International Journal
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In this paper, we consider the problem of color restoration using statistical priors. This is applied to color recovery for underwater images, using an energy minimization formulation. Underwater images present a challenge when trying to correct the blue-green monochrome look to bring out the color we know marine life has. For aquatic robot tasks, the quality of the images is crucial and needed in real-time. Our method enhances the color of the images by using a Markov Random Field (MRF) to represent the relationship between color depleted and color images. The parameters of the MRF model are learned from the training data and then the most probable color assignment for each pixel in the given color depleted image is inferred by using belief propagation (BP). This allows the system to adapt the color restoration algorithm to the current environmental conditions and also to the task requirements. Experimental results on a variety of underwater scenes demonstrate the feasibility of our method.