Local Belief Aggregation for Mrf-based Color Image Segmentation

The enormous number of segment label in color image segmentation causes MRF-based color segmentation algorithm to suffer from complexity and storage explosion. To cope with this problem, this paper proposed a local belief aggregation (LBA) algorithm which restricts the number of messages to be aggregated from a neighboring node. The LBA is applied to our MRF model, which is formulated based on the intra and inter region criteria, to find the segmentation image that approximate the MAP solution. Experiment results show that the proposed color image segmentation algorithm can achieve a comparable result to mean-shift algorithm both objectively and subjectively.