Title :
A new approach to texture coding using stochastic vector quantization
Author :
Gimeno, D. ; Torres, L. ; Casas, J.R.
Author_Institution :
Dept. de Teoria del Senyal i Comunicacions, Univ. Politecnica de Catalunya, Barcelona, Spain
Abstract :
A new method for texture coding which combines 2-D linear prediction and stochastic vector quantization is presented in this paper. To encode a texture, a linear predictor is computed first. Next, a codebook following the prediction error model is generated and the prediction error is encoded with VQ, using an algorithm which takes into account the pixels surrounding the block being encoded. In the decoder, the error image is decoded first and then filtered as a whole, using the prediction filter. Hence, correlation between pixels is not lost from one block to another and a good reproduction quality can be achieved
Keywords :
correlation methods; decoding; filtering theory; image coding; image texture; linear predictive coding; stochastic processes; vector quantisation; 2-D linear prediction; codebook; correlation; decoder; error image; image reproduction quality; linear predictor; pixels; prediction error model; prediction filter; stochastic vector quantization; texture coding; Algorithm design and analysis; Decoding; Filters; Image coding; Predictive models; Process design; Statistics; Stochastic processes; Terminology; Vector quantization;
Conference_Titel :
Image Processing, 1994. Proceedings. ICIP-94., IEEE International Conference
Conference_Location :
Austin, TX
Print_ISBN :
0-8186-6952-7
DOI :
10.1109/ICIP.1994.413287