Simulated annealing and Boltzmann machines: a stochastic approach to combinatorial optimization and neural computing
Reconstruction of a color image from nonuniformly distributed sparse and noisy data
CVGIP: Graphical Models and Image Processing
Results using random field models for the segmentation of color images of natural scenes
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
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We address the problem of color image restoration. We model the image as a Markov random field (MRF) and propose a restoration algorithm in a multiresolution framework. The incorporation of multiresolution technique significantly reduces the computational complexity of the restoration algorithm. The energy function at each resolution being non-convex, is minimized using the simulated annealing algorithm. The parameters which describe the MRF model at each resolution are computed a priori using the homotopy continuation method. Simulation results are presented to validate the proposed scheme.