MyJournals Home  

RSS FeedsRemote Sensing, Vol. 11, Pages 1169: An Energy-Based SAR Image Segmentation Method with Weighted Feature (Remote Sensing)


16 may 2019 15:03:10

Remote Sensing, Vol. 11, Pages 1169: An Energy-Based SAR Image Segmentation Method with Weighted Feature (Remote Sensing)

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. Digg Facebook Google StumbleUpon Twitter
43 viewsCategory: Geology, Physics
Remote Sensing, Vol. 11, Pages 1170: Analysis of the Spatiotemporal Variation in Land Subsidence on the Beijing Plain, China (Remote Sensing)
Remote Sensing, Vol. 11, Pages 1168: A Survey on Situational Awareness of Ransomware Attacks--Detection and Prevention Parameters (Remote Sensing)
blog comments powered by Disqus
The latest issues of all your favorite science journals on one page


Register | Retrieve



Use these buttons to bookmark us: Digg Facebook Google StumbleUpon Twitter

Valid HTML 4.01 Transitional
Copyright © 2008 - 2019 Indigonet Services B.V.. Contact: Tim Hulsen. Read here our privacy notice.
Other websites of Indigonet Services B.V.: Nieuws Vacatures News Tweets Travel Photos Nachrichten Indigonet Finances Leer Mandarijn