Title :
A Kalman filter for noise reduction on SAR imagery
Author :
Geling, Gary ; Ionescu, Dan
Author_Institution :
Dept. of Electr. Eng., Ottawa Univ., Ont., Canada
Abstract :
Despite the numerous applications that have been developed for synthetic aperture radar (SAR) images, their degradation due to the presence of noise makes them very difficult to use. Kalman filtering techniques have been investigated for various image models. Following a model suggested by Azimi-Sadjadi and Bannour (see IEEE Transactions on Geoscience and Remote Sensing, vol.29, no.5, p.742-753, 1991) we propose a modified Kalman technique for SAR imagery. The large variation of the statistics of the noise is compensated for by a variance to mean ratio. The Kalman filter gain is, therefore, adapted to the statistics of the local area. Comparisons with the method mentioned above are given for real ERS-1 SAR data collected from Victoria, BC
Keywords :
adaptive Kalman filters; adaptive signal processing; filtering theory; noise; radar imaging; synthetic aperture radar; ERS-1 SAR data; Kalman filter gain; Kalman filtering techniques; SAR imagery; SAR images; Victoria; image models; local area statistics; modified adaptive Kalman filter; noise reduction; noise statistics; synthetic aperture radar; variance to mean ratio; Adaptive Kalman filtering; Adaptive signal processing; Filtering; Noise; Radar imaging/mapping; Synthetic aperture radar;
Conference_Titel :
Electrical and Computer Engineering, 1994. Conference Proceedings. 1994 Canadian Conference on
Conference_Location :
Halifax, NS
Print_ISBN :
0-7803-2416-1
DOI :
10.1109/CCECE.1994.405774
