On a Kernels, Lévy Processes, and Natural Image Statistics

Publikation: Bidrag til bog/antologi/rapportKonferencebidrag i proceedingsForskningfagfællebedømt

The probability distribution on the set of naturally occurring images is sparse with most of the probability mass on a small subset of all possible images, hence not all images are equally likely to be seen in nature. This can indirectly be observed by studying the marginal statistics of filter responses on natural images. Intensity differences, or equivalently responses of linear filters, of natural images have a spiky distribution with heavy tails, which puts a large proportion of the probability mass on small intensity differences, but at the same time giving a reasonable probability on large differences. This is due to the fact that images consist mostly of smooth regions separated by discontinuous boundaries. We propose to model natural images as stochastic Lévy processes with agr kernel distributed intensity differences. We will argue that the scale invariant agr kernels of the recently proposed agr scale space theory provides a promising model of the intensity difference distribution (or in general linear filter responses) in conjunction with the Lévy process model of natural images.
TitelScale Space and PDE Methods in Computer Vision
Forlag<Forlag uden navn>
ISBN (Trykt)978-3-540-25547-5
StatusUdgivet - 2005
Eksternt udgivetJa
Begivenhed5th International Conference in Scale-Space - Hofgeismar, Tyskland
Varighed: 7 apr. 20059 apr. 2005
Konferencens nummer: 5


Konference5th International Conference in Scale-Space
NavnLecture notes in computer science

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Poster Presentation

ID: 4980169