Change Detection in Synthetic Aperture Radar Images based on Image Fusion and Fuzzy Clustering

This paper presents an unsupervised distribution-free change detection approach for synthetic aperture radar (SAR) images based on an image fusion strategy and a novel fuzzy clustering algorithm. The image fusion technique is introduced to generate a difference image by using complementary informati...

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Vydané v:IEEE transactions on image processing Ročník 21; číslo 4; s. 2141 - 2151
Hlavní autori: Gong, Maoguo, Zhou, Zhiqiang, Ma, Jingjing
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: United States IEEE 01.04.2012
Predmet:
Algorithms
Change detection algorithms
Clustering
Clustering algorithms
Damping
Discrete wavelet transforms
fuzzy C-means (FCM) algorithm
Fuzzy Logic
image change detection
Image Enhancement - methods
Image fusion
Image Interpretation, Computer-Assisted - methods
Imaging, Three-Dimensional - methods
Noise
Pattern Recognition, Automated - methods
Radar
Reproducibility of Results
Sensitivity and Specificity
Subtraction Technique
synthetic aperture radar (SAR)
Wavelet coefficients
ISSN:1057-7149, 1941-0042, 1941-0042
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Shrnutí:This paper presents an unsupervised distribution-free change detection approach for synthetic aperture radar (SAR) images based on an image fusion strategy and a novel fuzzy clustering algorithm. The image fusion technique is introduced to generate a difference image by using complementary information from a mean-ratio image and a log-ratio image. In order to restrain the background information and enhance the information of changed regions in the fused difference image, wavelet fusion rules based on an average operator and minimum local area energy are chosen to fuse the wavelet coefficients for a low-frequency band and a high-frequency band, respectively. A reformulated fuzzy local-information C-means clustering algorithm is proposed for classifying changed and unchanged regions in the fused difference image. It incorporates the information about spatial context in a novel fuzzy way for the purpose of enhancing the changed information and of reducing the effect of speckle noise. Experiments on real SAR images show that the image fusion strategy integrates the advantages of the log-ratio operator and the mean-ratio operator and gains a better performance. The change detection results obtained by the improved fuzzy clustering algorithm exhibited lower error than its preexistences.
Bibliografia:ObjectType-Article-1
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ISSN:1057-7149
1941-0042
1941-0042
DOI:10.1109/TIP.2011.2170702