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23 October 1996 Multiscale geometric filter based on the wavelet transform
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A viable approach to noise filtering in a spatially heterogeneous environment consists of considering a multiresolution representation of the noisy image, nd of applying a different adaptive filter to each layer. The wavelet decomposition has been widely employed, thanks to its capability to capture spatial features within frequency subbands. Geometric filter is a nonlinear local operator that exploits a morphologic approach to smooth noise using a complementary hull algorithm, which as the effect of gradually reducing the maximum curvature of the boundary of the grey-level profile along all of the 8-neighbor directions. The idea of the present scheme is to apply the complementary-hull algorithm to the different subbands into which the noisy image is decomposed. The hull is applied only on the direction along which the signal is structured. The number of iterations is adjusted to the SNR of the subbands, so as to preserve spatial details to the largest extent. Results and comparisons with the standard geometric filter are presented for images affected by synthetic multiplicative noise.
© (1996) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Luciano Alparone, Fabrizio Argenti, and Andrea Garzelli "Multiscale geometric filter based on the wavelet transform", Proc. SPIE 2825, Wavelet Applications in Signal and Image Processing IV, (23 October 1996);

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