SAR River Image Segmentation Based on Reciprocal Gray Entropy and Improved Chan-Vese Model

SAR River Image Segmentation Based on Reciprocal Gray Entropy and Improved Chan-Vese Model

To further improve the accuracy and speed of river segmentation on synthetic aperture radar(SAR) images, a segmentation method is proposed, which is based on improved Chan-Vese(CV) model combining with reciprocal gray entropy multi-threshold selection optimized by artificial bee colony algorithm. Co...

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Bibliographic Details
Main Authors: WU Shihua, WU Yiquan, ZHOU Jianjiang, MENG Tianliang
Format: Article
Language:zho
Published: Surveying and Mapping Press 2015-11-01
Series:Acta Geodaetica et Cartographica Sinica
Subjects:
river detection
synthetic aperture radar image segmentation
multi-threshold selection
reciprocal gray entropy
artificial bee colony optimization
Chan-Vese(CV)model
Online Access:http://html.rhhz.net/CHXB/html/2015-11-1255.htm

Internet

http://html.rhhz.net/CHXB/html/2015-11-1255.htm

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