Matrix thresholding for multiwavelet image denoising (original) (raw)

Vector thresholding is a recently proposed technique for the denoising of one-dimensional signals by means of multiwavelet shrinkage. It is more suited both to dealing with the multiwavelet vector coefficients and to taking into account the correlations which can be introduced among the starting vector coefficients by the use of a suitable prefilter. Motivated by the successful results of the multiwavelet transform when used in image processing, the aim of this paper is to extend vector thresholding to the two-dimensional case by introducing the notion of matrix thresholding. This new method allows us to easily exploit the "matrix" nature of the two-dimensional multiwavelet transform, and represents the natural extension of vector thresholding to the 2-D case. Afterwards, as the choice of the threshold level is very important in the practical application of thresholding methods, we propose a first attempt to extend the recently introduced method of H-curve to a multiple wavelet setting. The results of extensive numerical simulations confirm the effectiveness of our proposals and encourage us to keep going in this direction with further studies.