A-contrario ringing detection and Shannon-compliant images

Gwendoline Blanchet (1) , Lionel Moisan (2) , Bernard Rougé (3)

1 CNES - Centre National d'Études Spatiales [Toulouse]
2 MAP5 - UMR 8145 - Mathématiques Appliquées Paris 5
3 CMLA - Centre de Mathématiques et de Leurs Applications

According to Shannon Sampling Theory, cardinal sine (sinc) interpolation is the optimal way to reach subpixel accuracy from a properly sampled digital image. However, for most images sinc interpolation tends to produce an artifact called ringing, that consists in undesirable oscillations near objects contours. In this work, we propose a way to detect this ringing artifact in an a-contrario framework. Using Euler zigzag numbers, we compute the probability that neighboring gray-levels form an alternating sequence by chance, and characterize this way ringing blocks as structures that would be very unlikely in a random image. We then show two applications where the associated algorithm is used to test or enforce the compliance of an image with sinc interpolation.

Mots clés: Shannon sampling Theory; ringing; sinc interpolation; Euler zigzag numbers; a-contrario detection

Domaines: Traitement des images [eess.IV]

Gwendoline Blanchet, Lionel Moisan, Bernard Rougé. A-contrario ringing detection and Shannon-compliant images. 2009. ⟨hal-00388032v1⟩