A Threshold Selection Method Using Two SAR Change Detection Measures Based on the Markov Random Field Model

Author

Xiong, Boli ; Chen, Qi ; Jiang, Yongmei ; Kuang, Gangyao

Author_Institution

Sch. of Electron. Sci. & Eng., Nat. Univ. of Defense Technol., Changsha, China

Volume

9

Issue

2

fYear

2012

fDate

3/1/2012 12:00:00 AM

Firstpage

287

Lastpage

291

Abstract

This letter presents a threshold selection method in change detection (CD) with synthetic aperture radar (SAR) images, which combines the characteristics of two different CD measures by using the Markov random field model. One is the well-known log-ratio CD measure, and the other is derived from the likelihood ratio and is based on the statistical properties of SAR intensity images. The proposed unsupervised CD algorithm overcomes the shortcomings and strengthens the advantages of these two measures. The experimental results with two pairs of SAR images show that the proposed algorithm is effective and better than the algorithms using the two aforementioned CD measures.

Keywords

Markov processes; image segmentation; radar imaging; statistical analysis; synthetic aperture radar; Markov random field model; SAR change detection measure; SAR intensity image; likelihood ratio; log-ratio CD measure; statistical property; synthetic aperture radar image; threshold selection method; unsupervised CD algorithm; Hidden Markov models; Histograms; Markov processes; Monitoring; Remote sensing; Speckle; Synthetic aperture radar; Change detection (CD); Markov random field (MRF); synthetic aperture radar (SAR) image; threshold selection;

fLanguage

English

Journal_Title

Geoscience and Remote Sensing Letters, IEEE

Publisher

ieee

ISSN

1545-598X

Type

jour

DOI

10.1109/LGRS.2011.2166149

Filename

6035957