DocumentCode :
1341461
Title :
Change Detection in Synthetic Aperture Radar Images based on Image Fusion and Fuzzy Clustering
Author :
Gong, Maoguo ; Zhou, Zhiqiang ; Ma, Jingjing
Author_Institution :
Key Lab. of Intell. Perception & Image Understanding of Minist. of Educ., Xidian Univ., Xi´´an, China
Volume :
21
Issue :
4
fYear :
2012
fDate :
4/1/2012 12:00:00 AM
Firstpage :
2141
Lastpage :
2151
Abstract :
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.
Keywords :
radar imaging; synthetic aperture radar; complementary information; fuzzy clustering; image fusion; mean ratio image; synthetic aperture radar images; unsupervised distribution free change detection; Change detection algorithms; Clustering algorithms; Damping; Discrete wavelet transforms; Image fusion; Noise; Wavelet coefficients; Clustering; fuzzy C-means (FCM) algorithm; image change detection; image fusion; synthetic aperture radar (SAR); Algorithms; Fuzzy Logic; Image Enhancement; Image Interpretation, Computer-Assisted; Imaging, Three-Dimensional; Pattern Recognition, Automated; Radar; Reproducibility of Results; Sensitivity and Specificity; Subtraction Technique;
fLanguage :
English
Journal_Title :
Image Processing, IEEE Transactions on
Publisher :
ieee
ISSN :
1057-7149
Type :
jour
DOI :
10.1109/TIP.2011.2170702
Filename :
6035777
Link To Document :
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