USE OF DARWINIAN PARTICLE SWARM OPTIMIZATION TECHNIQUE FOR THE SEGMENTATION OF REMOTE SENSING IMAGES

被引：19

作者：

Ghamisi, Pedram ^{[1
]}

Couceiro, Micael S. ^{[1
]}

Ferreira, Nuno M. F. ^{[1
]}

Kumar, Lalit ^{[1
]}

机构：

[1] KN Toosi Univ Technol, Geodesy & Geomat Engn Fac, Tehran, Iran

来源：

2012 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS) | 2012年

关键词：

multilevel segmentation; swarm optimization; remote sensing;

D O I：

10.1109/IGARSS.2012.6351718

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

In this work, a novel method for segmentation of Remote Sensing (RS) images based on the Darwinian Particle Swarm Optimization (DPSO) for determining the n-1 optimal n-level threshold on a given image is proposed. The efficiency of the proposed method is compared with the Particle Swarm Optimization (PSO) based segmentation method. Results show that DPSO-based image segmentation performs better than PSO-based method in a number of different measures.

引用

页码：4295 / 4298

页数：4

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