Image set compression with eigenvectors spectral representation

Alexandr G. Chumakov; Vitalij N. Kurashov

doi:10.1117/12.228229

8 December 1995 Image set compression with eigenvectors spectral representation

Alexandr G. Chumakov, Vitalij N. Kurashov

Proceedings Volume 2605, Coding and Signal Processing for Information Storage; (1995) https://doi.org/10.1117/12.228229
Event: Photonics East '95, 1995, Philadelphia, PA, United States

Abstract

In this work the new spectral representation for noisy images is investigated. The orthogonal image expansion is based on the eigenvectors of symmetric CK-criterion which takes into account both correlation properties of signal and noise ensembles. We suppose that such representation provides maximal concentration of noiseless image in main spectral components, and so the effective noise suppression under spectrum truncation can be achieved. An effective algorithm for KL and CK-eigenvectors calculation has been proposed. Performed numerical experiments verify the algorithm efficiency and its suitability for image processing problems.

Citation Download Citation

Alexandr G. Chumakov and Vitalij N. Kurashov "Image set compression with eigenvectors spectral representation", Proc. SPIE 2605, Coding and Signal Processing for Information Storage, (8 December 1995); https://doi.org/10.1117/12.228229

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