NDLI: Contourlet HMT model with directional feature

Content Provider	Springer Nature Link
Author	Wang, XiangHai Chen, MingYing Song, ChuanMing Xu, MengChun Fang, LingLing
Copyright Year	2012
Abstract	According to Shanno’s information theory, the directional feature of texture is defined as the value of directional variable when an image signal attains a singularity of random distribution. In terms of this definition, we calculate the texture’s directional features using Tamura’s method and study the directional probability distribution of Contourlet coefficients. Then we find that the directional features tend to be conveyed across parent and child subbands. Based on this conclusion, we establish a novel probability distribution model of hidden direction variables under the condition of hidden state variable’s distribution, named Contourlet HMT model with directional feature. The structure and training method of the model are presented as well. Moreover, an unsupervised context-based image segmentation algorithm is proposed on the basis of the proposed model. Its effectiveness is verified via extensive experiments carried out on several synthesized images and remote sensing images.
Starting Page	1563
Ending Page	1578
Page Count	16
File Format	PDF
ISSN	1674733X
Journal	Science in China Series : Information Sciences
Volume Number	55
Issue Number	7
e-ISSN	18691919
Language	English
Publisher	SP Science China Press
Publisher Date	2012-06-19
Publisher Place	Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	directional feature Contourlet HMT Contourlet HMT with directional feature unsupervised texture segmentation Information Systems and Communication Service
Content Type	Text
Resource Type	Article
Subject	Computer Science

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