Automatic detection of well sampled images via a new ringing measure

According to Shannon Sampling Theory, Fourier interpolation is the optimal way to reach subpixel accuracy from a properly-sampled digital image. However, for most images this 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. Using Euler zigzag numbers, we compute the probability that neighboring gray-levels form an alternating sequence by chance, and characterize these undesirable 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 Fourier interpolation.

• Type: Conference
• Year: 2010
• Where: ICASSP
• Authors: Gwendoline Blanchet, Lionel Moisan, Bernard Rougé
• Keywords: Fourier Interpolation, ICASSP 2010, Image, Shannon Sampling Theory, Signal Processing