Compounding segmentation method for SAR images

Zhang Jinping; Zhao Wei; Cheng Gong; Mao Shiyi

doi:10.1109/ICOSP.2006.345991

Compounding segmentation method for SAR images

Zhang Jinping^*
, Zhao Wei
, Cheng Gong
, Mao Shiyi

^*Corresponding author for this work

School of Electronic and Information Engineering

Beihang University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Fast and accurate segmentation of synthetic aperture radar (SAR) images is important to SAR automatic target recognition (ATR). In this paper, a new compounding segmentation method is presented, based on the two-parameter CFA R segmentation method and Markov Random Field (MRF) -based segmentation approach. Following the initial segmentation obtained by the two-parameter CFAR method, the MRF-based approach is exploited only on the edge points of the targets and shadows. A comparative experimental analysis, using MSTAR (Moving and Stationary Target Acquisition and Recognition) images, of the proposed method against the other two approaches showed that the compounding segmentation method can achieve faster and more accurate results, which can be of practical use in the process of SAR ATR.

Original language	English
Title of host publication	8th International Conference on Signal Processing, ICSP 2006
DOIs	https://doi.org/10.1109/ICOSP.2006.345991
State	Published - 2007
Event	8th International Conference on Signal Processing, ICSP 2006 - Guilin, China Duration: 16 Nov 2006 → 20 Nov 2006

Publication series

Name	International Conference on Signal Processing Proceedings, ICSP
Volume	4

Conference

Conference	8th International Conference on Signal Processing, ICSP 2006
Country/Territory	China
City	Guilin
Period	16/11/06 → 20/11/06

Access to Document

10.1109/ICOSP.2006.345991

Cite this

@inproceedings{dedef21aea2d43fa994d69737da6b489,

title = "Compounding segmentation method for SAR images",

abstract = "Fast and accurate segmentation of synthetic aperture radar (SAR) images is important to SAR automatic target recognition (ATR). In this paper, a new compounding segmentation method is presented, based on the two-parameter CFA R segmentation method and Markov Random Field (MRF) -based segmentation approach. Following the initial segmentation obtained by the two-parameter CFAR method, the MRF-based approach is exploited only on the edge points of the targets and shadows. A comparative experimental analysis, using MSTAR (Moving and Stationary Target Acquisition and Recognition) images, of the proposed method against the other two approaches showed that the compounding segmentation method can achieve faster and more accurate results, which can be of practical use in the process of SAR ATR.",

author = "Zhang Jinping and Zhao Wei and Cheng Gong and Mao Shiyi",

year = "2007",

doi = "10.1109/ICOSP.2006.345991",

language = "英语",

isbn = "0780397371",

series = "International Conference on Signal Processing Proceedings, ICSP",

booktitle = "8th International Conference on Signal Processing, ICSP 2006",

note = "8th International Conference on Signal Processing, ICSP 2006 ; Conference date: 16-11-2006 Through 20-11-2006",

}

TY - GEN

T1 - Compounding segmentation method for SAR images

AU - Jinping, Zhang

AU - Wei, Zhao

AU - Gong, Cheng

AU - Shiyi, Mao

PY - 2007

Y1 - 2007

N2 - Fast and accurate segmentation of synthetic aperture radar (SAR) images is important to SAR automatic target recognition (ATR). In this paper, a new compounding segmentation method is presented, based on the two-parameter CFA R segmentation method and Markov Random Field (MRF) -based segmentation approach. Following the initial segmentation obtained by the two-parameter CFAR method, the MRF-based approach is exploited only on the edge points of the targets and shadows. A comparative experimental analysis, using MSTAR (Moving and Stationary Target Acquisition and Recognition) images, of the proposed method against the other two approaches showed that the compounding segmentation method can achieve faster and more accurate results, which can be of practical use in the process of SAR ATR.

AB - Fast and accurate segmentation of synthetic aperture radar (SAR) images is important to SAR automatic target recognition (ATR). In this paper, a new compounding segmentation method is presented, based on the two-parameter CFA R segmentation method and Markov Random Field (MRF) -based segmentation approach. Following the initial segmentation obtained by the two-parameter CFAR method, the MRF-based approach is exploited only on the edge points of the targets and shadows. A comparative experimental analysis, using MSTAR (Moving and Stationary Target Acquisition and Recognition) images, of the proposed method against the other two approaches showed that the compounding segmentation method can achieve faster and more accurate results, which can be of practical use in the process of SAR ATR.

UR - https://www.scopus.com/pages/publications/34249310258

U2 - 10.1109/ICOSP.2006.345991

DO - 10.1109/ICOSP.2006.345991

M3 - 会议稿件

AN - SCOPUS:34249310258

SN - 0780397371

SN - 9780780397378

T3 - International Conference on Signal Processing Proceedings, ICSP

BT - 8th International Conference on Signal Processing, ICSP 2006

T2 - 8th International Conference on Signal Processing, ICSP 2006

Y2 - 16 November 2006 through 20 November 2006

ER -

Compounding segmentation method for SAR images

Abstract

Publication series

Conference

Access to Document

Other files and links

Fingerprint

Cite this