Redesigning of JPEG statistical model in the lossy mode fitting distribution of DCT coefficients

The JPEG statistical models in the lossy mode specify the procedures for converting the discrete cosine transform (DCT) coefficients into binary strings and context modeling in the case where the binary arithmetic coder called the QM-coder is employed as an entropy coder. The JPEG lossy mode establi...

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Bibliographic Details
Published in:Proceedings 2000 International Conference on Image Processing (Cat. No.00CH37101) Vol. 3; pp. 825 - 828 vol.3
Main Authors: Kuroki, Y., Ueshige, Y., Ohta, T.
Format: Conference Proceeding
Language:English
Published: IEEE 2000
Subjects:
Arithmetic
Context modeling
Discrete cosine transforms
Discrete transforms
Laplace equations
Pixel
Probability
Statistical analysis
Statistical distributions
Testing
ISBN:0780362977, 9780780362970
ISSN:1522-4880
Online Access:Get full text
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Summary:The JPEG statistical models in the lossy mode specify the procedures for converting the discrete cosine transform (DCT) coefficients into binary strings and context modeling in the case where the binary arithmetic coder called the QM-coder is employed as an entropy coder. The JPEG lossy mode establishes two statistical models, one for prediction residuals of the DC coefficients and the other for the AC coefficients. We redesign these two models by taking account of their distribution. We confirm that the Laplacian distribution is appropriate for both the DC coefficients and the AC coefficients through the Kolmogorov-Smirnov (KS) test; consequently, we propose statistical models that fit the Laplacian distribution. By adopting the proposed statistical models in lieu of the conventional models, the number of the states decreases from 294 to 210 and the compression performance on several test images including super high definition images improves by 0.01 to 1.48%.
ISBN:0780362977
9780780362970
ISSN:1522-4880
DOI:10.1109/ICIP.2000.899583