Use of the angle information in the wavelet transform maxima for image de-noising

摘要

In this article, a new method of de-noising is proposed, based on the wavelet maxima. The originality of this method is in the use of the gradient angle in a multi-scale framework as the discriminatory parameter. In order to use to the best advantage the angle information, the multi-scale gradient decomposition schema proposed by Mallat is modified thus enabling a computation of uncorrelated partial derivatives. From this computation, a selection method of multi-scale contours is put forward, having a lesser algorithmic complexity than processings based on the gradient norm. The performance of this new algorithm is illustrated using simulated data and angiography images.