By Topic

MPM SAR Image Segmentation Using Feature Extraction and Context Model

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Biao Hou ; Key Lab. of Intell. Perception & Image Understanding of the Minist. of Educ. of China, Xidian Univ., Xi'an, China ; Xiangrong Zhang ; Nan Li

A new synthetic aperture radar (SAR) image segmentation method based on a maximization of posterior marginals (MPM) algorithm with feature extraction and context model is proposed in this letter. First, Gabor wavelet and texture descriptor are used to extract features, which enhance intraclass similarities and interclass differences. Second, the number of regions within the same class is reduced in order to improve the reliability of the regional statistical characteristics. Finally, the MPM of each region combined with the context model is calculated by considering both the intralayer correlation and interlayer correlation. The experimental results show that the proposed method is efficient and effective for SAR image segmentation.

Published in:

Geoscience and Remote Sensing Letters, IEEE  (Volume:9 ,  Issue: 6 )