Local Phase Coherence and the Perception of Blur
Presented (as a talk) at:
Neural Information Processing Systems (NIPS*03), Vancouver BC, Dec 2003.
To appear in:
Advances in Neural Information Processing Systems 16
eds. S. Thrun, L. Saul, and B. Schölkopf, May 2004.
© MIT Press, Cambridge, MA.
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.
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