Hierarchical region based Markov random field for image segmentation

Author

Mei, Tiancan ; Zheng, Chen ; Zhong, Sidong

Author_Institution

Sch. of Electron. Inf., Wuhan Univ., Wuhan, China

fYear

2011

fDate

24-26 June 2011

Firstpage

381

Lastpage

384

Abstract

In the pixel based multiscale Markov random field(MRF) model, a sequence of MRF was hierarchically defined on the multiple spatial resolutions which might suffer from the deficiency of modeling the large range of interaction. In order to overcome such a problem, we attempt to introduce the region based multiscale MRF model, in which hierarchical MRF model is defined over multiresolution image segmented regions. Based on regional multiscale MRF model, supervised image segmentation algorithm is presented and experiment on natural scene image demonstrate the better performance than the pixel based multiscale MRF model.

Keywords

Markov processes; image resolution; image segmentation; random processes; hierarchical multiscale MRF model; hierarchical multiscale Markov random fleld model; image resolution; image segmentation algorithm; multiple spatial resolution; Computational modeling; Image segmentation; Labeling; Markov processes; Pixel; Wavelet transforms; Hierarchical Markov random field model; Region based image segmentation; Sequential maximum a posteriori;

fLanguage

English

Publisher

ieee

Conference_Titel

Remote Sensing, Environment and Transportation Engineering (RSETE), 2011 International Conference on

Conference_Location

Nanjing

Print_ISBN

978-1-4244-9172-8

Type

conf

DOI

10.1109/RSETE.2011.5964293

Filename

5964293