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A novel approach to robust blind classification of remote sensing imagery

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3 Author(s)
Kundur, D. ; Dept. of Electr. & Comput. Eng., Toronto Univ., Ont., Canada ; Hatzinakos, D. ; Leung, H.

We propose a novel method for the robust classification of blurred and noisy images that incorporates ideas from data fusion. The technique is applicable to blind situations in which the exact blurring function is unknown. The approach treats differently deblurred versions of the same image as distinct correlated sensor readings of the same scene. The images are fused during the classification process to provide a more reliable result. We show analytically that the various restorations can be treated as images acquired from different but correlated sensor readings. Experimental results demonstrate the potential of the method for robust classification of imagery

Published in:

Image Processing, 1997. Proceedings., International Conference on  (Volume:3 )

Date of Conference:

26-29 Oct 1997