Image analysis through local information measures

Author

Bruce, Neil

Author_Institution

Dept. of Comput. Sci., York Univ., Toronto, Ont., Canada

Volume

1

fYear

2004

fDate

23-26 Aug. 2004

Firstpage

616

Abstract

The properties of local image statistics are analyzed in a classic information theoretic setting. Local spatiochromatic image elements are projected into a space in which constituent components are independent by way of independent component analysis, allowing a fast and tractable means of considering the joint likelihood of such statistics. Observation of this likelihood allows inferences to be made regarding the informativeness of a particular set of statistics. This operation is shown to illuminate a number of perceptually important image properties, allowing figure-ground segmentation, removal of common or expected image elements, and prediction of regions of interest.

Keywords

image colour analysis; image segmentation; independent component analysis; information theory; figure-ground segmentation; image analysis; image properties; independent component analysis; joint likelihood; local image statistics; local information measures; local spatiochromatic image elements; regions of interest; Computer science; Image analysis; Image coding; Image segmentation; Independent component analysis; Information analysis; Information theory; Probability; Statistical analysis; Statistics;

fLanguage

English

Publisher

ieee

Conference_Titel

Pattern Recognition, 2004. ICPR 2004. Proceedings of the 17th International Conference on

ISSN

1051-4651

Print_ISBN

0-7695-2128-2

Type

conf

DOI

10.1109/ICPR.2004.1334223

Filename

1334223