A novel variational model for retinex in presence of severe noises

Two-Stage Image Segmentation Scheme Based on Inexact Alternating Direction Method

AbstractImage segmentation is a fundamental problem in both image processing and computer vision with numerous applications. In this paper, we propose a two-stage image segmentation scheme based on inexact alternating direction method. Specifically, we first solve the convex variant of the Mumford-Shah model to get the smooth solution, the segmentation are then obtained by apply the K-means clustering method to the solution. Some numerical comparisons are arranged to show the effectiveness of our proposed schemes by segmenting many kinds of images such as artificial images, natural images, and brain MRI images.

Alternating split Bregman method for the bilaterally constrained image deblurring problem

Fast algorithm for multiplicative noise removal

Semismooth Newton method for minimization of the LLT model