Unsupervised change detection in SAR images based on Gauss log ratio image fusion NSCT analysis and compressed projection - A, Aneesa Fathima; Sunny, Liya Elizabeth (IJRDO -Journal of Computer Science Engineering, 2015)
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.