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An Energy-Based SAR Image Segmentation Method with Weighted Feature

College of Geomatics and Geoinformation, Guilin University of Technology, Guilin 541004, China
Author to whom correspondence should be addressed.
Remote Sens. 2019, 11(10), 1169;
Received: 27 March 2019 / Revised: 7 May 2019 / Accepted: 10 May 2019 / Published: 16 May 2019
(This article belongs to the Section Remote Sensing Image Processing)
PDF [2994 KB, uploaded 16 May 2019]


To extract more structural features, which can contribute to segment a synthetic aperture radar (SAR) image accurately, and explore their roles in the segmentation procedure, this paper presents an energy-based SAR image segmentation method with weighted features. To precisely segment a SAR image, multiple structural features are incorporated into a block- and energy-based segmentation model in weighted way. In this paper, the multiple features of a pixel, involving spectral feature obtained from original SAR image, texture and boundary features extracted by a curvelet transform, form a feature vector. All the pixels’ feature vectors form a feature set of a SAR image. To automatically determine the roles of the multiple features in the segmentation procedure, weight variables are assigned to them. All the weight variables form a weight set. Then the image domain is partitioned into a set of blocks by regular tessellation. Afterwards, an energy function and a non-constrained Gibbs probability distribution are used to combine the feature and weight sets to build a block-based energy segmentation model with feature weighted on the partitioned image domain. Further, a reversible jump Markov Chain Monte Carlo (RJMCMC) algorithm is designed to simulate from the segmentation model. In the RJMCMC algorithm, three move types were designed according to the segmentation model. Finally, the proposed method was tested on the SAR images, and the quantitative and qualitative results demonstrated its effectiveness. View Full-Text
Keywords: SAR image segmentation with weighted feature; energy function; curvelet feature; RJMCMC algorithm SAR image segmentation with weighted feature; energy function; curvelet feature; RJMCMC algorithm

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Wang, Y.; Zhou, G.; You, H. An Energy-Based SAR Image Segmentation Method with Weighted Feature. Remote Sens. 2019, 11, 1169.

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