The principal components of natural images revisited

Author

Heidemann, Gunther

Author_Institution

Dept. of Electr. & Comput. Eng., Florida State Univ., Tallahassee, FL, USA

Volume

28

Issue

5

fYear

2006

fDate

5/1/2006 12:00:00 AM

Firstpage

822

Lastpage

826

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.

Keywords

band-pass filters; image colour analysis; principal component analysis; bandpass filters; natural color images; natural gray images; principal components; spatio-chromatic structure; Color; Computer vision; Eigenvalues and eigenfunctions; Filters; Frequency; Image databases; Personal communication networks; Pixel; Shape measurement; Spatial databases; Statistical image representation; color scene analysis; computational models of vision; computer vision; connectionism and neural nets.; feature measurement; feature representation; shape; texture; Algorithms; Artificial Intelligence; Image Enhancement; Image Interpretation, Computer-Assisted; Information Storage and Retrieval; Pattern Recognition, Automated; Principal Component Analysis;

fLanguage

English

Journal_Title

Pattern Analysis and Machine Intelligence, IEEE Transactions on

Publisher

ieee

ISSN

0162-8828

Type

jour

DOI

10.1109/TPAMI.2006.107

Filename

1608044