Title :
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
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;
Conference_Titel :
Remote Sensing, Environment and Transportation Engineering (RSETE), 2011 International Conference on
Conference_Location :
Nanjing
Print_ISBN :
978-1-4244-9172-8
DOI :
10.1109/RSETE.2011.5964293
