A deterministic iterative algorithm for HMRF-textured image segmentation
Mahdad Nouri Shirazi, Hideki Noda · 2005
The problem of textured image segmentation is considered. A textured image is modeled by a hierarchical Markov random field (HMRF). The image segmentation is realized as the maximum a posteriori (MAP) estimate of the textured regions. Following an argument based on the mean field approximation, a deterministic iterative algorithm is proposed which searches for the MAP segmentation of the textured image.