Progressively adaptive scalar quantization

Author

Wong, Ping Wah

Author_Institution

Hewlett-Packard Co., Palo Alto, CA, USA

Volume

1

fYear

1996

fDate

16-19 Sep 1996

Firstpage

357

Abstract

We consider a progressively adaptive scalar quantization scheme where the quantizer is adjusted as input samples are processed. The quantizer adjustments are based on an estimated probability density function (pdf) consisting of piecewise polynomials. This pdf is calculated from the bin probabilities that are estimated from quantized samples. The effect of the support of the pdf on the performance of Lloyd-Max quantizers is also examined. Experimental results on the progressively adaptive quantizer for non-stationary sources are shown

Keywords

adaptive signal processing; estimation theory; image coding; image sampling; piecewise polynomial techniques; probability; quantisation (signal); Lloyd-Max quantizers; adaptive quantizer; bin probabilities; estimated probability density function; input samples; nonstationary sources; piecewise polynomials; progressively adaptive scalar quantization scheme; quantizer adjustments; Adaptive systems; Arithmetic; Density functional theory; Huffman coding; Laboratories; Milling machines; Piecewise linear techniques; Polynomials; Probability density function; Quantization;

fLanguage

English

Publisher

ieee

Conference_Titel

Image Processing, 1996. Proceedings., International Conference on

Conference_Location

Lausanne

Print_ISBN

0-7803-3259-8

Type

conf

DOI

10.1109/ICIP.1996.560832

Filename

560832