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Multiplicative waveforms decomposition

Serir A.

Machine Graphics and Vision

2000

Vol. 9, No. 1/2

389-396

This paper introduces a nonel nonlinear low-level representation of an image with signal-dependent noise. For multiplicative noisy image, we introduce an algorithm called multiplicative matching pursuit decomposition MMPD, that decomposes the signal containing the intrinsic variation into a nonlinear expansion of waveforms that are selected from redundant dictionary of functions to best match the signal local structures. The convergence of this new multiplicative decoposition has been proved and tested in practice. An application to speckle reduction in SAR images is described.