Synthetic aperture radar image segmentation using non‐linear diffusion‐based hierarchical triplet Markov fields model-Reference-Cited by-同舟云学术

Synthetic aperture radar image segmentation using non‐linear diffusion‐based hierarchical triplet Markov fields model

Published:2017-10-24 Issue:12 Volume:11 Page:1302-1309
ISSN:1751-9659
Container-title:IET Image Processing
language:en
Short-container-title:IET image process

Author:

Wang Fan¹,Wu Yan¹,Zhang Peng²,Liang Wenkai¹,Li Ming²

Affiliation:

1. Remote Sensing Image Processing and Fusion Group, School of Electronics Engineering, Xidian UniversityP.O. Box 140Xi'an710071People's Republic of China

2. National Key Laboratory of Radar Signal ProcessingXidian UniversityXi'an710071People's Republic of China

Funder

National Natural Science Foundation of China

Publisher

Institution of Engineering and Technology (IET)

Subject

Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Signal Processing,Software

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/iet-ipr.2016.0901

Reference16 articles.

1. Fine logarithmic adaptive soft morphological algorithm for synthetic aperture radar image segmentation

2. Adaptive Bayesian contextual classification based on Markov random fields

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4. Sonar image segmentation using an unsupervised hierarchical MRF model;Mignotte M.;IEEE Trans. Image Process.,2000

5. Unsupervised segmentation of synthetic aperture Radar sea ice imagery using a novel Markov random field model

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