DocumentCode
1900040
Title
Correlation Model for Uniform Scalar Quantizers with Arbitrary Representation Levels
Author
Hjørungnes, Are ; Yahampath, Pradeepa ; Pawlak, Mirek
Author_Institution
Univ. of Oslo, Oslo
fYear
2007
fDate
10-12 June 2007
Firstpage
1
Lastpage
4
Abstract
This article derives closed-form expressions for correlation values of quantization errors in a set of uniform quantizers with arbitrary representation levels, operating on a vector of Gaussian stochastic variables. The problem is relevant to subband coding of random vectors using linear filter hunks, a technique that may be useful fur lossy compression of micro-array images. The results obtained here generalize previous results in which the representation levels are constrained to be midpoints of uniform quantization intervals. In particular, a set of expressions for auto-and cross-correlation values of the quantization error vector are derived. Monte-Carlo simulations are used to verify the validity of the given expressions, which indicate a very good match between numerical results and the values predicted by the derived expressions.
Keywords
Monte Carlo methods; channel bank filters; correlation methods; filtering theory; image coding; quantisation (signal); Gaussian stochastic variables; Monte-Carlo simulations; arbitrary representation levels; closed-form expressions; correlation model; linear filter banks; microarray image compression; quantization errors; random vectors; subband coding; uniform scalar quantizers; Additive noise; Autocorrelation; Bioinformatics; Filter bank; Finite impulse response filter; Genomics; Image coding; Noise generators; Quantization; Vectors; Uniform quantizers; arbitrary representation levels; auto-correlation; cross-correlation;
fLanguage
English
Publisher
ieee
Conference_Titel
Genomic Signal Processing and Statistics, 2007. GENSIPS 2007. IEEE International Workshop on
Conference_Location
Tuusula
Print_ISBN
978-1-4244-0998-3
Electronic_ISBN
978-1-4244-0999-0
Type
conf
DOI
10.1109/GENSIPS.2007.4365816
Filename
4365816
Link To Document