Image Segmentation Based on Class Adaptive Spatially Variant Mixture Model

This paper proposes an image segmentation method which allocates regional smoothness automatically according to the requirements.The method improves existing class adaptive spatially variant mixture model based on revising the potential function in Markov random field and introducing colorful or grey feature information into the assessment of segmentation regions.As a result,the stability by the revised method is improved significantly.Meanwhile,the added pixel strength coefficients to the method increase its flexibility and practical value greatly.Finally,the algorithm efficiency is approved through experimental simulation on the test images from MIT and Berkeley galley.