DocumentCode :
3047382
Title :
The researches of the image segmentation algorithm based on Contourlet transformation
Author :
Xiao Yihan ; Xi Zhihong ; Hai Tao ; Guo Liang
Author_Institution :
Inf. & Commun. Eng. Coll., Harbin Eng. Univ., Harbin, China
fYear :
2010
fDate :
20-23 June 2010
Firstpage :
1700
Lastpage :
1704
Abstract :
The image Segmentation is resulted, by Wavelet Domain Hidden Markov Tree model, dim edge components prone and diffuse singularity. The Contourlet transformation can capture the singularity in the image of high dimension, therefore, the paper presents a new algorithm of multiscale image segmentation based on the Contourlet transform. This algorithm was initially segmented in scales by Contourlet domain Hidden Markov Tree Model, and integrated among multiscales after segmentting images through the adaptive context structures. Compared simulating segmentation experiment of synthetic texture image and aerial image to Wavelet Domain Hidden Markov Tree Model image segmentation method, we obtain more desirable segmentation effect with the regional consistency and edge accuracy, and the composed images with lower misclassification rate.
Keywords :
hidden Markov models; image segmentation; maximum likelihood estimation; trees (mathematics); wavelet transforms; Contourlet transform; adaptive context structures; aerial image; edge accuracy; multiscale image segmentation; regional consistency; synthetic texture image; wavelet domain hidden Markov tree model; Context modeling; Educational institutions; Hidden Markov models; Image analysis; Image representation; Image resolution; Image segmentation; Maximum likelihood estimation; Wavelet domain; Wavelet transforms;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information and Automation (ICIA), 2010 IEEE International Conference on
Conference_Location :
Harbin
Print_ISBN :
978-1-4244-5701-4
Type :
conf
DOI :
10.1109/ICINFA.2010.5512231
Filename :
5512231
Link To Document :
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