Showing papers by "Antoni Buades published in 2008"

Nonlocal Image and Movie Denoising

Abstract: Neighborhood filters are nonlocal image and movie filters which reduce the noise by averaging similar pixels. The first object of the paper is to present a unified theory of these filters and reliable criteria to compare them to other filter classes. A CCD noise model will be presented justifying the involvement of neighborhood filters. A classification of neighborhood filters will be proposed, including classical image and movie denoising methods and discussing further a recently introduced neighborhood filter, NL-means. In order to compare denoising methods three principles will be discussed. The first principle, "method noise", specifies that only noise must be removed from an image. A second principle will be introduced, "noise to noise", according to which a denoising method must transform a white noise into a white noise. Contrarily to "method noise", this principle, which characterizes artifact-free methods, eliminates any subjectivity and can be checked by mathematical arguments and Fourier analysis. "Noise to noise" will be proven to rule out most denoising methods, with the exception of neighborhood filters. This is why a third and new comparison principle, the "statistical optimality", is needed and will be introduced to compare the performance of all neighborhood filters. The three principles will be applied to compare ten different image and movie denoising methods. It will be first shown that only wavelet thresholding methods and NL-means give an acceptable method noise. Second, that neighborhood filters are the only ones to satisfy the "noise to noise" principle. Third, that among them NL-means is closest to statistical optimality. A particular attention will be paid to the application of the statistical optimality criterion for movie denoising methods. It will be pointed out that current movie denoising methods are motion compensated neighborhood filters. This amounts to say that they are neighborhood filters and that the ideal neighborhood of a pixel is its trajectory. Unfortunately the aperture problem makes it impossible to estimate ground true trajectories. It will be demonstrated that computing trajectories and restricting the neighborhood to them is harmful for denoising purposes and that space-time NL-means preserves more movie details.

Method for processing a digital object and related system

Abstract: The invention relates to the processing of a digital object that comprises: cancelling the noise of an original object (I) of a first type containing noise in order to obtain a noise-free object (J) of the first type; obtaining an object with a quasi-white noise of the first type from a difference (B) between the original object and the noise-free object; applying to the noise-free object (J) a first processing (t1) that comprises a neighbouring processing for obtaining a transformed object (K) of a second type, the first processing being such that it would structure the noise contained in the original object if it was applied to said original object; applying to the noise object a second white processing (t2) for obtaining a quasi-white transformed noise object (C) of the second type; and inserting into the transformed object (K) the transformed noise object.

Procede de traitement d'objet numerique et systeme associe

Abstract: Traitement d'objet numerique, dans lequel : on debruite un objet original (I) d'un premier type contenant du bruit pour obtenir un objet debruite (J) dudit premier type; on obtient un objet de bruit quasi blanc du premier type a partir d'une difference (B) entre l'objet original et l'objet debruite; on applique a l'objet debruite (J) un premier traitement (tl) comprenant un traitement a voisinage pour obtenir un objet transforme (K) d'un deuxieme type, le premier traitement etant tel qu'il aurait pour effet de structurer le bruit contenu dans l'objet original s'il etait applique audit objet original; on applique a l'objet de bruit un deuxieme traitement (t2) blanc pour obtenir un objet de bruit transforme (C) quasi blanc du deuxieme type; et,- on introduit dans l'objet transforme (K) l'objet de bruit transforme.