Automatic Change Analysis in Satellite Images Using Binary Descriptors and Lloyd–Max Quantization
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Automatic Change Analysis in Satellite Images Using Binary Descriptors and Lloyd–Max Quantization
Abstract— Automatic Change Analysis in Satellite Images Using Binary Descriptors and Lloyd–Max Quantization. A novel technique for un-supervised change analysis that leads to a method of ranking the changes that occur between two satellite images acquired at dif-ferent moments of time. The proposed change analysis is based on binary descriptors and uses the Hamming distance as a similarity metric. In order to render a completely unsupervised solution, the obtained distances are further classified using vector quantization methods i.e., Lloyd’s algorithm for optimal quantization. < Final Year Projects 2016 > The ultimate goal in the change analysis chain is to build change intensity maps that provide an overview of the severeness of changes in the area under analysis.
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