1 June 1990 Two-dimensional code excited linear prediction image coding system
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Abstract
This paper presents a two-dimensional code excited linear prediction (CELP) method for image coding. This method is a two-dimensional extension of the CELP systems commonly used for speech coding. The decoder is identical to a conventional DPCM decoder. However, at the encoder, the input images are first decomposed into disjoint blocks. A single codeword from a table of N codewords is used to represent the vector of quantized residuals for each block. The encoder selects the appropriate codeword by reconstructing N versions of the current block, using each of the N vectors of the codebook. The index of the codeword giving the least distortion is then transmitted. In designing the codebook, while the LBG method of clustering failed to converge, we have succeeded in finding a deterministic codebook based on a training set using the method of successive clustering. The system has been extended by using adaptive prediction, where one of K possible prediction filters is used for each block; the encoder chooses the prediction filter that results in the least mean squared prediction error. An index is transmitted to the decoder indicating which prediction filter has been used. With no additional overhead, K different codebooks can be used, corresponding to each of the prediction filters. We have tested this system using five predictors. The five predictors were initially selected to give good performance on different types of image material, e.g. edges of different orientation, and then refined by minimizing the mean square prediction error on those pixels for which the initial predictor gave the lowest mean square error.
© (1990) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Hung Q. Nguyen, Eric Dubois, "Two-dimensional code excited linear prediction image coding system", Proc. SPIE 1244, Image Processing Algorithms and Techniques, (1 June 1990); doi: 10.1117/12.19510; http://dx.doi.org/10.1117/12.19510
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KEYWORDS
Image compression

Computer programming

Quantization

Distortion

Image filtering

Image processing

Digital filtering

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