An Efficient Laplacian-Model Based Dequantization for Uniformly Quantized DCT Coefficients

Kwang-Deok SEO  Kook-Yeol YOO  Jae-Kyoon KIM  

Publication
IEICE TRANSACTIONS on Information and Systems   Vol.E85-D   No.2   pp.421-425
Publication Date: 2002/02/01
Online ISSN: 
DOI: 
Print ISSN: 0916-8532
Type of Manuscript: LETTER
Category: Image Processing, Image Pattern Recognition
Keyword: 
quantization,  image compression,  Laplacian model,  JPEG,  MPEG,  

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Summary: 
Quantization is an essential step which leads to compression in discrete cosine transform (DCT) domain. In this paper, we show how a statistically non-optimal uniform quantizer can be improved by employing an efficient reconstruction method. For this purpose, we estimate the probability distribution function (PDF) of original DCT coefficients in a decoder. By applying the estimated PDF into the reconstruction process, the dequantization distortion can be reduced. The proposed method can be used practically in any applications where uniform quantizers are used. In particular, it can be used for the quantization scheme of the JPEG and MPEG coding standards.