Variational method of speckle reduction and boundary detection in SAR imagery

Zhipeng Xia; Xiaona Tang; Fang Li; Guixu Zhang

doi:10.1117/12.813242

Variational method of speckle reduction and boundary detection in SAR imagery

Zhipeng Xia
, Xiaona Tang
, Fang Li
, Guixu Zhang^*

^*Corresponding author for this work

East China Normal University

Research output: Contribution to journal › Conference article › peer-review

1 Scopus citations

Abstract

Synthetic Aperture Radar (SAR) images have been widely used in remote sensing applications. However, the SAR image contains speckle noise. In this paper, we propose a variational method to delineate the boundary of objects in SAR images. It is implemented by two steps: The first step is speckle reduction and the second step is boundary detection. The two steps are implemented with a unified frame of energy minimization. In each step, we define an energy functional, and the corresponding minimizer of the functional is regarded as the result. An ERS-2 PRecision Image (PRI) over Proserpine area in Australia is used to demonstrate the algorithm. The results of both steps appear to be very promising.

Original language	English
Article number	714715
Journal	Proceedings of SPIE - The International Society for Optical Engineering
Volume	7147
DOIs	https://doi.org/10.1117/12.813242
State	Published - 2008
Event	Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Classification of Remote Sensing Images - Guangzhou, China Duration: 28 Jun 2008 → 29 Jun 2008

Keywords

Chan-Vese model
Image decomposition
SAR
Variational method

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10.1117/12.813242

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title = "Variational method of speckle reduction and boundary detection in SAR imagery",

abstract = "Synthetic Aperture Radar (SAR) images have been widely used in remote sensing applications. However, the SAR image contains speckle noise. In this paper, we propose a variational method to delineate the boundary of objects in SAR images. It is implemented by two steps: The first step is speckle reduction and the second step is boundary detection. The two steps are implemented with a unified frame of energy minimization. In each step, we define an energy functional, and the corresponding minimizer of the functional is regarded as the result. An ERS-2 PRecision Image (PRI) over Proserpine area in Australia is used to demonstrate the algorithm. The results of both steps appear to be very promising.",

keywords = "Chan-Vese model, Image decomposition, SAR, Variational method",

author = "Zhipeng Xia and Xiaona Tang and Fang Li and Guixu Zhang",

year = "2008",

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language = "英语",

volume = "7147",

journal = "Proceedings of SPIE - The International Society for Optical Engineering",

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note = "Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Classification of Remote Sensing Images ; Conference date: 28-06-2008 Through 29-06-2008",

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TY - JOUR

T1 - Variational method of speckle reduction and boundary detection in SAR imagery

AU - Xia, Zhipeng

AU - Tang, Xiaona

AU - Li, Fang

AU - Zhang, Guixu

PY - 2008

Y1 - 2008

N2 - Synthetic Aperture Radar (SAR) images have been widely used in remote sensing applications. However, the SAR image contains speckle noise. In this paper, we propose a variational method to delineate the boundary of objects in SAR images. It is implemented by two steps: The first step is speckle reduction and the second step is boundary detection. The two steps are implemented with a unified frame of energy minimization. In each step, we define an energy functional, and the corresponding minimizer of the functional is regarded as the result. An ERS-2 PRecision Image (PRI) over Proserpine area in Australia is used to demonstrate the algorithm. The results of both steps appear to be very promising.

AB - Synthetic Aperture Radar (SAR) images have been widely used in remote sensing applications. However, the SAR image contains speckle noise. In this paper, we propose a variational method to delineate the boundary of objects in SAR images. It is implemented by two steps: The first step is speckle reduction and the second step is boundary detection. The two steps are implemented with a unified frame of energy minimization. In each step, we define an energy functional, and the corresponding minimizer of the functional is regarded as the result. An ERS-2 PRecision Image (PRI) over Proserpine area in Australia is used to demonstrate the algorithm. The results of both steps appear to be very promising.

KW - Chan-Vese model

KW - Image decomposition

KW - SAR

KW - Variational method

UR - https://www.scopus.com/pages/publications/62449253744

U2 - 10.1117/12.813242

DO - 10.1117/12.813242

M3 - 会议文章

AN - SCOPUS:62449253744

SN - 0277-786X

VL - 7147

JO - Proceedings of SPIE - The International Society for Optical Engineering

JF - Proceedings of SPIE - The International Society for Optical Engineering

M1 - 714715

T2 - Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Classification of Remote Sensing Images

Y2 - 28 June 2008 through 29 June 2008

ER -

Variational method of speckle reduction and boundary detection in SAR imagery

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Keywords

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