A unifying framework for natural image statistics: spatiotemporal activity bubbles

Reference:

Aapo Hyvärinen, Jarmo Hurri, and Jaakko Väyrynen. A unifying framework for natural image statistics: spatiotemporal activity bubbles. Neurocomputing, 58–60:801–806, 2004.

Abstract:

Recently, different models of the statistical structure of natural images (and sequences) have been proposed. Maximizing sparseness, or alternatively temporal coherence of linear filter outputs leads to the emergence of simple cell properties. Taking account of the basic dependencies of linear filter outputs enables modelling of complex cell and topographic properties as well. Here, we propose a unifying framework for all these statistical properties, based on the concept of spatiotemporal activity bubbles.

Keywords:

natural image statistics, simple cells, sparse coding, independent component analysis, temporal coherence

Suggested BibTeX entry:

@article{Hyvarinen04NC,
    author = {Aapo Hyv{\"{a}}rinen and Jarmo Hurri and Jaakko V{\"{a}}yrynen},
    journal = {Neurocomputing},
    pages = {801--806},
    title = {A unifying framework for natural image statistics: spatiotemporal activity bubbles},
    volume = {58--60},
    year = {2004},
}