A Segmentation Algorithm for Noisy Images

This paper presents a segmentation algorithm for gray-level images and addresses issues related to its performance on noisy images. It formulates an image segmentation problem as a partition of a weighted image neighborhood hypergraph. To overcome the computational difficulty of directly solving this problem, a multilevel hypergraph partitioning has been used. To evaluate the algorithm, we have studied how noise affects the performance of the algorithm. The α-stable noise is considered and its effects on the algorithm are studied. Key words : graph, hypergraph, neighborhood hypergraph, multilevel hypergraph partitioning, image segmentation and noise removal.

• Type: Conference
• Year: 2005
• Where: CAIP
• Authors: Soufiane Rital, Hocine Cherifi, Serge Miguet
• Keywords: CAIP 2005, Image Neighborhood Hypergraph, Multilevel Hypergraph Partitioning, Neighborhood Hypergraph