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Proceedings Paper

Karhunen-Loeve Algorithm For Time-Rescaled Gaussian Processes
Author(s): Claudio Maccone
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Paper Abstract

The Karhunen-Loeve (K-L) expansion is largerly used in digital picture compression. We present a new algorithm to compute the K-L eigenfunctions and eigenvalues for a Gaussian stochastic process whose time elapses according to an arbitrary law rather than uniformly. These eigenfunctions are proved to be time-rescaled Bessel functions of the first kind having their order depending on the time. The K-L eigenvalues are proved to be the zeros of a linear combination involving the Bessel functions and their partial derivatives of the first order. Also, a study is made of the energy of the time-rescaled Gaussian processes, and we show that the analytical treatment can be pushed up to the cumulants of the energy distribution. Moreover, we have found the relationship between the time-rescaling function and the velocity of a relativistically moving body, that is, we have related the K-L expansion to both the special and the general theory of relativity. This appears to pave the way to a general method for the K-L compression in the digital picture processing of a relativistic source.

Paper Details

Date Published: 2 March 1989
PDF: 13 pages
Proc. SPIE 1027, Image Processing II, (2 March 1989); doi: 10.1117/12.950276
Show Author Affiliations
Claudio Maccone, AERITALIA S.A.I.p.A. (Italy)


Published in SPIE Proceedings Vol. 1027:
Image Processing II
Peter J.S. Hutzler; Andre J. Oosterlinck, Editor(s)

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