Lossless Image Compression by Two-Dimensional Linear Prediction with Variable Coefficients

Nobutaka KUROKI  Takanori NOMURA  Masahiro TOMITA  Kotaro HIRANO  

Publication
IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences   Vol.E75-A    No.7    pp.882-889
Publication Date: 1992/07/25
Online ISSN: 
DOI: 
Print ISSN: 0916-8508
Type of Manuscript: Special Section PAPER (Special Section on Multidimensional Signal Processing)
Category: Image Coding and Compression
Keyword: 
lossless image coding,  image compression,  2D linear prediction,  

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Summary: 
A lossless image compression method based on two-dimensional (2D) linear prediction with variable coefficients is proposed. This method employs a space varying autoregressive (AR) model. To achieve a higher compression ratio, the method introduces new ideas in three points: the level conversion, the fast recursive parameter estimation, and the switching method for coding table. The level conversion prevents an AR model from predicting gray-level which does not exist in an image. The fast recursive parameter estimation algorithm proposed here calculates varying coefficients of linear prediction at each pixel in shorter time than conventional one. For encoding, the mean square error between the predicted value and the true one is calculated in the local area. This value is used to switch the coding table at each pixel to adapt it to the local statistical characteristics of an image. By applying the proposed method to "Girl" and "Couple" of IEEE monochromatic standard images, the compression ratios of 100 : 46 and 100 : 44 have been achieved, respectively. These results are superior to the best results (100 : 61 and 100 : 57) obtained by the approach under JPEG recommendations.