Title :
Evaluating time correlation of speckle in ERS-1 SAR images
Author :
Alparone, Luciano ; Baronti, Stefano ; Garzelli, Andrea
Author_Institution :
Dept. of Electron. Eng., Florence Univ., Italy
Abstract :
A novel method is proposed to automatically measure the temporal correlation coefficient (TCC) of speckle from a set of SAR images of the same scene taken at different times. The knowledge of the TCC of speckle may expedite the detection and assessment of seasonal changes having occurred. In addition, it provides an upper bound to the maximum SNR increase achievable by multitemporal processing. A nonlinear transformation aimed at decorrelating the data across time, while retaining the multiplicative noise model, is defined. The TCC is estimated from the modes of the distributions of the local variation coefficient (Cv) computed on the transformed images. Tests on SAR images (both synthetic and from ERS-1) show the accuracy and the robustness of the method, whose results are unaffected by underlying seasonal changes occurring across observations
Keywords :
geophysical signal processing; geophysical techniques; radar imaging; remote sensing by radar; spaceborne radar; speckle; synthetic aperture radar; ERS-1; SAR image; geophysical measurement technique; land surface; local variation coefficient; multiplicative noise model; multitemporal processing; nonlinear transformation; radar imaging; radar remote sensing; seasonal change detection; spaceborne radar; speckle time correlation; synthetic aperture radar; temporal correlation coefficient; terrain mapping; Decorrelation; Distributed computing; Electromagnetic measurements; Electromagnetic scattering; Layout; Pixel; Signal to noise ratio; Speckle; Testing; Upper bound;
Conference_Titel :
Geoscience and Remote Sensing Symposium Proceedings, 1998. IGARSS '98. 1998 IEEE International
Conference_Location :
Seattle, WA
Print_ISBN :
0-7803-4403-0
DOI :
10.1109/IGARSS.1998.702787