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Proceedings Paper

DPCM Quantization Error Reduction For Image Coding
Author(s): William K. Pratt; Michael N. Huhns
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Paper Abstract

A method for optimally reducing the error incurred during the quantization operation in DPCM image coding is presented. The method is optimum with respect to a mean-square error criterion and is applied a posteriori. The technique is based on knowledge of the multidimensional probability density function of the DPCM difference signal. The quantizer operates on this difference signal to achieve a data compression. The coarser the quantization, the greater the compression, but also the greater the degradation of the encoded image. To minimize the degradation, a reconstruction should utilize all of the knowledge that is available about the difference samples, such as their distribution, the quantization levels, and any correlation which remains after the differencing operation. An estimation equation which embodies this information is derived and solved. The solution is applied to images which have been either DPCM or deltamodulation encoded. The resultant images have lower mean-square error and exhibit an improvement in subjective quality.

Paper Details

Date Published: 30 October 1975
PDF: 5 pages
Proc. SPIE 0066, Efficient Transmission of Pictorial Information, (30 October 1975); doi: 10.1117/12.965360
Show Author Affiliations
William K. Pratt, University of Southern California (United States)
Michael N. Huhns, University of Southern California (United States)

Published in SPIE Proceedings Vol. 0066:
Efficient Transmission of Pictorial Information
Andrew G. Tescher, Editor(s)

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