This chapter presents an analysis of the current status and the challenges in change detection techniques for the analysis of multitemporal SAR images. Algorithms and methods based on validated statistical models for SAR data are investigated, which adopt advanced information-theoretic and multi-scale signal-processing methodologies. After a brief review of the recent literature on general change detection methods, the chapter investigates the specific problem of change detection in SAR images. The main properties of the change detection problem in SAR images are explored and discussed. Then, recent change detection techniques for high-resolution (HR) and very high-resolution (VHR) SAR data are presented and critically analyzed from the theoretical viewpoint. Finally, examples of application of these techniques to real problems are presented by using simulated image pairs and Enhanced Spotlight COSMO-SkyMed images.
|Titolo:||Change detection in multitemporal images through single- and multi-scale approaches|
GARZELLI, ANDREA (Corresponding)
|Citazione:||Aiazzi, B., Bovolo, F., Bruzzone, L., Garzelli, A., Pirrone, D., & Zoppetti, C. (2018). Change detection in multitemporal images through single- and multi-scale approaches. In J.Z. G. Moser G. (a cura di), Mathematical Models for Remote Sensing Image Processing. Models and Methods for the Analysis of 2D Satellite and Aerial Images. (pp. 325-355). Cham : Springer.|
|Appare nelle tipologie:||2.1 Contributo in volume (Capitolo o Saggio)|
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