Image codec by noncausal prediction, residual mean removal, and cascaded VQ

1 January 1996

journal article
Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Circuits and Systems for Video Technology

Vol. 6 (1) , 42-55
https://doi.org/10.1109/76.486419

Abstract

We describe a technique for still image compression that combines (i) noncausal optimal recursive prediction, (ii) residual quadtree mean removal, and (iii) a modification of cascaded vector quantization. We refer to this image codec as noncausal prediction with residual mean removal, and cascaded vector quantization (NRQ/CVQ). We provide examples that illustrate the performance of NRQ/CVQ up to compression ratios of 42.5:1. We show that NRQ/CVQ outperforms alternative algorithms that we tested including the conventional causal prediction differential pulse code modulation (DPCM) with quadtree mean removal cascaded vector quantization and the Joint Photographic Experts Group (JPEG) baseline standard algorithm

Keywords

This publication has 11 references indexed in Scilit:

Variable block-size image coding
Published by Institute of Electrical and Electronics Engineers (IEEE) ,2005
Multiple stage vector quantization for speech coding
Published by Institute of Electrical and Electronics Engineers (IEEE) ,2005
Noncausal Gauss Markov random fields: parameter structure and estimation
IEEE Transactions on Information Theory, 1993
Vector quantizers with direct sum codebooks
IEEE Transactions on Information Theory, 1993
The JPEG still picture compression standard
Communications of the ACM, 1991
Recursive Block Coding for Image Data Compression
Published by Springer Nature ,1990
Least squares quantization in PCM
IEEE Transactions on Information Theory, 1982
An Algorithm for Vector Quantizer Design
IEEE Transactions on Communications, 1980
DPCM Picture Coding with Adaptive Prediction
IEEE Transactions on Communications, 1977
Two-dimensional discrete Markovian fields
IEEE Transactions on Information Theory, 1972