Multiregion level-set partitioning of synthetic aperture radar images

被引：151

作者：

Ben Ayed, I

Mitiche, A

Belhadj, Z

机构：

[1] INRS EMT, Montreal, PQ H5A 1K6, Canada

[2] Ecole Super Commun Tunis SUP COM, Tunis 2083, Tunisia

来源：

IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE | 2005年 / 27卷 / 05期

基金：

加拿大自然科学与工程研究理事会;

关键词：

image segmentation; active contours; level sets; statistical modeling; synthetic aperture radar;

D O I：

10.1109/TPAMI.2005.106

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The purpose of this study is to investigate Synthetic Aperture Radar (SAR) image segmentation into a given but arbitrary number of gamma homogeneous regions via active contours and level sets. The segmentation of SAR images is a difficult problem due to the presence of speckle which can be modeled as strong, multiplicative noise. The proposed algorithm consists of evolving simple closed planar curves within an explicit correspondence between the interiors of curves and regions of segmentation to minimize a criterion containing a term of conformity of data to a speckle model of noise and a term of regularization. Results are shown on both synthetic and real images.

引用

页码：793 / 800

页数：8

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