Natural Image Statistics

← Back to document page

Aapo Hyv arinenJarmo HurriPatrik O. HoyerNatural Image StatisticsA probabilistic approach to earlycomputational visionFebruary 27, 2009SpringerContents overview1Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .1Part I Background2Linear filters and frequency analysis. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 253Outline of the visual system. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 514Multivariate probability and Statistics . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69Part II Statistics of linear features5Principal components and whitening. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 976Sparse coding and simple cells.

Aapo Hyv¨arinen Jarmo Hurri Patrik O. Hoyer Natural Image Statistics A probabilistic approach to early computational vision February 27, 2009 Springer

  Statistics, Image, Natural, Natural image statistics