Title :
Image segmentation using Directionlet-domain hidden Markov tree models
Author :
Bai, Jing ; Zhao, Jiaqi ; Jiao, Lc
Author_Institution :
Key Lab. of Intell. Perception & Image Understanding of Minist. of Educ. of China, Xidian Univ., Xi´´an, China
Abstract :
In this paper, we modeled the Directionlet coefficients of an image using hidden Markov tree (HMT) model and obtained the image segmentation results using model parameter training, multi-scale likelihood computation and the background of neighborhood-based maximum posterior probability. We demonstrate the performance of the proposed method with synthetic mosaic images and SAR images. The experiment results showed that our method obtained more exact boundary and uniform regions.
Keywords :
hidden Markov models; image segmentation; radar imaging; synthetic aperture radar; trees (mathematics); Directionlet-domain hidden Markov tree models; SAR images; image segmentation; model parameter training; multiscale likelihood computation; neighborhood-based maximum posterior probability; synthetic mosaic images; Computational modeling; Hidden Markov models; Image edge detection; Image segmentation; Synthetic aperture radar; Training; Transforms; Contourlet; Directionlet; Hidden Markov tree(HMT); Image segmentation;
Conference_Titel :
Radar (Radar), 2011 IEEE CIE International Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4244-8444-7
DOI :
10.1109/CIE-Radar.2011.6159874
