Unsupervised change detection in SAR images based on Gauss log ratio image fusion NSCT analysis and compressed projection
Abstract
Multitemporal synthetic aperture radar (SAR)
images helps in detecting different types of terrain changes.
Due to the presence of speckle noise and complex terrain
detecting the changes in SAR images has become a complex
task. In this paper an unsupervised method for detecting the
changes in SAR images has been proposed. First Gauss log
operator and log operator are applied on the SAR images to
obtain the difference image. Image fusion and then image de
noising is performed on the difference image using Non
subsampled counter let transform (NSCT).Compressed
projection is performed to extract the feature vectors. Finally
the feature vectors are partitioned by using Fuzzy clustering
approach into two classes, changed class and unchanged class.
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