On optimal low-rank approximation of multidimensional discrete signals

Author

Lu, Wu-Sheng ; Pei, S.-C.

Author_Institution

Dept. of Electr. & Comput. Eng., Victoria Univ., BC, Canada

Volume

45

Issue

3

fYear

1998

fDate

3/1/1998 12:00:00 AM

Firstpage

417

Lastpage

422

Abstract

This brief describes an algorithmic development of the optimal low-rank approximation (LRA) of multidimensional (M-D) signals with M⩾3. The algorithms developed can be regarded as a dimensional generalization of the singular value decomposition (SVD) which is of fundamental importance for analyzing signals that can be represented in a matrix form. In particular, iterative algorithms for optimal and suboptimal LRA of three-dimensional (3-D) arrays are presented in detail. Application of the 3-D LRA to the compression of image sequences is discussed

Keywords

data compression; image sequences; iterative methods; singular value decomposition; 3D arrays; dimensional generalization; image sequence compression; iterative algorithms; matrix form; multidimensional discrete signals; optimal low-rank approximation; singular value decomposition; Approximation algorithms; CMOS technology; Discrete transforms; Iterative algorithms; Multidimensional systems; Signal processing algorithms; Singular value decomposition; Temperature; Tensile stress; Voltage;

fLanguage

English

Journal_Title

Circuits and Systems II: Analog and Digital Signal Processing, IEEE Transactions on

Publisher

ieee

ISSN

1057-7130

Type

jour

DOI

10.1109/82.664254

Filename

664254