Properties of Brownian Image Models in Scale-Space

9 Citations (Scopus)

Abstract

In this paper it is argued that the Brownian image model is the least committed, scale invariant, statistical image model which describes the second order statistics of natural images. Various properties of three different types of Gaussian image models (white noise, Brownian and fractional Brownian images) will be discussed in relation to linear scale-space theory, and it will be shown empirically that the second order statistics of natural images mapped into jet space may, within some scale interval, be modeled by the Brownian image model. This is consistent with the 1/f 2 power spectrum law that apparently governs natural images. Furthermore, the distribution of Brownian images mapped into jet space is Gaussian and an analytical expression can be derived for the covariance matrix of Brownian images in jet space. This matrix is also a good approximation of the covariance matrix of natural images in jet space. The consequence of these results is that the Brownian image model can be used as a least committed model of the covariance structure of the distribution of natural images.
Original languageEnglish
Title of host publicationScale Space Methods in Computer Vision : 4th International Conference, Scale Space 2003 Isle of Skye, UK, June 10–12, 2003 Proceedings
Publisher<Forlag uden navn>
Publication date2003
Pages281-296
ISBN (Print)978-3-540-40368-5
DOIs
Publication statusPublished - 2003
Event4th International Conference in Scale Space - Isle of Skye, United Kingdom
Duration: 29 Nov 2010 → …
Conference number: 4

Conference

Conference4th International Conference in Scale Space
Number4
Country/TerritoryUnited Kingdom
CityIsle of Skye
Period29/11/2010 → …
SeriesLecture notes in computer science
Volume2695/2003
ISSN0302-9743

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