Synthetic aperture radar image segmentation using fuzzy label field‐based triplet Markov fields model
Author:
Affiliation:
1. School of Electronic Engineering, Xidian UniversityXi'an710071People's Republic of China
2. National 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.2013.0686
Reference15 articles.
1. Unsupervised segmentation of synthetic aperture Radar sea ice imagery using a novel Markov random field model
2. Unsupervised Statistical Segmentation of Nonstationary Images Using Triplet Markov Fields
3. Unsupervised multi‐class segmentation of SAR images using triplet Markov fields models based on edge penalty;Wu Y.;Pattern Recognit.,2011
4. SAR image multiclass segmentation using a multiscale TMF model in wavelet domain;Zhang P.;IEEE Geosci. Remote Sens. Lett.,2012
5. Unsupervised multi‐class segmentation of SAR images using fuzzy triplet Markov fields model;Zhang P.;Pattern Recognit.,2012
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