Compression of image clusters using Karhunen Loeve transformations | Zendy

Matthias Kramm | Zendy

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Compression of image clusters using Karhunen Loeve transformations

Author(s) -

Matthias Kramm

Publication year - 2007

Publication title -

proceedings of spie, the international society for optical engineering/proceedings of spie

Language(s) - English

Resource type - Conference proceedings

SCImago Journal Rank - 0.192

H-Index - 176

eISSN - 1996-756X

pISSN - 0277-786X

DOI - 10.1117/12.703992

Subject(s) - karhunen–loève theorem , discrete cosine transform , image compression , computer science , data compression , artificial intelligence , transform coding , computer vision , transformation (genetics) , image (mathematics) , compression (physics) , pattern recognition (psychology) , algorithm , image processing , biochemistry , chemistry , materials science , composite material , gene

This paper proposes to extend the Karhunen-Loeve compression algorithm to multiple images. The resulting algorithm is compared against single-image Karhunen Loeve as well as algorithms based on the Discrete Cosine Transformation (DCT). Futhermore, various methods for obtaining compressable clusters from large image databases are evaluated.

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