Advances in Neural Information Processing Systems, (NIPS03,
Local Phase Coherence and
the Perception of Blur
Zhou
Wang and Eero P. Simoncelli
Howard Hughes Medical Institute, Center for Neural
Science and Courant Institute of Mathematical Sciences, New York University,
New York, NY 10003
Abstract: Humans
are able to detect blurring of visual images, but the mechanism by which they
do so is not clear. A traditional view is that a blurred image looks “unnatural”
because of the reduction in energy (either globally or locally) at high
frequencies. In this paper, we propose that the disruption of local phase can provide
an alternative explanation for blur perception. We show that precisely
localized features such as step edges result in strong local phase coherence
structures across scale and space in the complex wavelet transform domain, and
blurring causes loss of such phase coherence. We propose a technique for
coarse-to-fine phase prediction of wavelet coefficients, and observe that (1) such
predictions are highly effective in natural images, (2) phase coherence
increases with the strength of image features, and (3) blurring disrupts the
phase coherence relationship in images. We thus lay the groundwork for a new
theory of perceptual blur estimation, as well as a variety of algorithms for
restoration and manipulation of photographic images..