Content-matched geometric filtering of image subbands for edge-preserving noise reduction

The idea of the present scheme is to apply a directional version of geometric filter (complementary-hull) to the different sub-bands into which the noisy image is decomposed by the S-transform, a dyadic Haar wavelet yielding integer valued coefficients. The hull algorithm is applied only on the direction(s) along which the signal is more structured. The number of iterations is adjusted to the SNR of the sub-bands, so as to preserve spatial details to the largest extent. Comparisons with the standard geometric filter are presented for images affected by synthetic multiplicative (speckle) noise. Results are pretty superior to those achieved without multiresolution context, both visually and in terms of SNR