Title :
Progressively adaptive scalar quantization
Author_Institution :
Hewlett-Packard Co., Palo Alto, CA, USA
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;
Conference_Titel :
Image Processing, 1996. Proceedings., International Conference on
Conference_Location :
Lausanne
Print_ISBN :
0-7803-3259-8
DOI :
10.1109/ICIP.1996.560832
