The principal components of natural images revisited.

IEEE transactions on pattern analysis and machine intelligence ·Vol. 28 ·No. 5 ·2006-05-00 ·Pages 822-6

Heidemann G

Abstract

This paper investigates the principal components (PCs) of natural gray and color images. A horizontal and vertical typology of PCs is found which leads to the identification of groups of basis functions for steerable bandpass filters. Using this system, the contribution of spatio-chromatic structure to the total variance can be quantified for selected spatial frequencies.

MeSH Terms

Algorithms Artificial Intelligence Image Enhancement/methods Image Interpretation, Computer-Assisted/methods Information Storage and Retrieval/methods Pattern Recognition, Automated/methods Principal Component Analysis

Authors & Affiliations

1 authors, click to expand affiliations / ORCID

Heidemann Gunther

Department of Electrical and Computer Engineering, Florida A&M University, Tallahassee 32310, USA. [email protected]

Article Info

Journal

IEEE transactions on pattern analysis and machine intelligence

Abbr.

IEEE Trans Pattern Anal Mach Intell

ISSN

0162-8828

DOI

10.1109/TPAMI.2006.107

[email protected]

Published

2006-05-00

Pages

822-6

Language

English

Region

United States

NLM ID

9885960

Subset

External Links

PubMed source DOI: 10.1109/TPAMI.2006.107 View journal details

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The principal components of natural images revisited.

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