Tree-Structured MRF Based Image Segmentation Combined with Advanced Means Shift Mode Detection
Liye Sun, Kanzhi Wu · 2011
Image segmentation is a critical issue in image understanding and several achievements have been achieved in this area. In this paper, we propose an improved image segmentation algorithm based on mean shift mode detection and Tree-Structured MRF (TS-MRF) model, which we believe is better. Section.2 briefs the mean shift mode detection and the speeded up KNN based mean shift algorithm used in the experiment. Section.3 presents the background knowledge of MRF model and TS-MRF model. On the basis of section.2 and section.3, we apply mean shift algorithm with bandwidth parameter h to calculate the number of clusters n. Then, we set n as the input parameter in MRF based segmentation and get n children nodes. The structure of the tree is formed by conducting above procedures iteratively. The result, shown in Fig.8 through 12 and their analysis demonstrate preliminarily that our novel algorithm is significantly better and still can be improved further.