Reference:

Aapo Hyvärinen, Jarmo Hurri, and Jaakko Väyrynen. Bubbles: A unifying framework for low-level statistical properties of natural image sequences. Journal of the Optical Society of America A, 20(7):1237–1252, 2003. Reprinted in Virtual Journal of Biological Physics Research, 6(2), 2003.

Abstract:

Recently, different models of the statistical structure of natural images have been proposed. These models predict properties of biological visual systems and can be used as priors in Bayesian inference. The fundamental model is independent component analysis, which can be estimated by maximization of the sparsenesses of linear filter outputs. This leads to the emergence of principal simple cell properties. Alternatively, simple cell properties are obtained by maximizing the temporal coherence in natural image sequences. Taking account of the basic dependencies of linear filter outputs permit modeling of complex cells and topographic organization as well. We propose a unifying framework for these statistical properties, based on the concept of spatiotemporal activity "bubbles." A bubble means here an activation of simple cells (linear filters) that is contiguous both in space (the cortical surface) and in time.

Keywords:

low vision, vision modeling, vision system neurophysiology

Suggested BibTeX entry:

@article{Hyvarinen03JOSA,
    author = {Aapo Hyv{\"{a}}rinen and Jarmo Hurri and Jaakko V{\"{a}}yrynen},
    journal = {Journal of the Optical Society of America A},
    note = {Reprinted in Virtual Journal of Biological Physics Research, 6(2), 2003},
    number = {7},
    pages = {1237--1252},
    title = {Bubbles: A unifying framework for low-level statistical properties of natural image sequences},
    volume = {20},
    year = {2003},
}