An Extension of the Student's t-distribution Mixture Model and the Gradient Descent method

Abstract

A new Student's t-distribution finite mixture model is proposed which incorporates the local spatial information of the pixels. The pixels' label probability proportions are explicitly modelled as probability vectors in the proposed model. We use the gradient descend method to estimate the parameters of the proposed model. Compre- hensive experiments are performed for synthetic and natural grayscale images. The experimental results demonstrate that the superiority of the proposed model over some other models. Index Terms—Spatially variant finite mixture model, Stu- dent's t-distribution, Image segmentation, Gradient descent