Multitemporal image change detection with compressed sparse representation


In this paper, we propose a novel feature vector clustering method for unsupervised change detection in multitemporal satellite images. A feature vector for each pixel is extracted using the compressed sparse representation of the difference image which is obtained by comparing a pair of co-registered images acquired at different times on the same area. The… (More)
DOI: 10.1109/ICIP.2011.6116218


5 Figures and Tables

Slides referencing similar topics