IMAGE DENOISING USING SIMILARITIES IN THE TIME SCALE PLANE

This paper presents a de-noising method that recognizes similarities in the image through the time scale behaviour of wavelet coefficients. Wavelet details are represented as linear combination of predefined atoms whose center of mass traces trajectories in the time scale plane (from fine to coarse scale). These trajectories are the solution of a proper ordinary differential equation and characterize atoms corresponding to groups of not isolated singularities in the signal. The distances among atoms, the ratio of their amplitudes and the difference of their decay along scales are the parameters to use for defining similarities in the image. Experimental results show the potentialities of the method in terms of visual quality and mean square error, reaching the most powerful and recent de-noising schemes.