Rate-distortion methods for image and video compression
- 1 November 1998
- journal article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Signal Processing Magazine
- Vol. 15 (6) , 23-50
- https://doi.org/10.1109/79.733495
Abstract
In this article we provide an overview of rate-distortion (R-D) based optimization techniques and their practical application to image and video coding. We begin with a short discussion of classical rate-distortion theory and then we show how in many practical coding scenarios, such as in standards-compliant coding environments, resource allocation can be put in an R-D framework. We then introduce two popular techniques for resource allocation, namely, Lagrangian optimization and dynamic programming. After a discussion of these techniques as well as some of their extensions, we conclude with a quick review of literature in these areas citing a number of applications related to image and video compression and transmission.Keywords
This publication has 92 references indexed in Scilit:
- Space-frequency quantization for wavelet image codingIEEE Transactions on Image Processing, 1997
- MPEG Video Compression StandardPublished by Springer Nature ,1997
- Digital PicturesPublished by Springer Nature ,1995
- Embedded image coding using zerotrees of wavelet coefficientsIEEE Transactions on Signal Processing, 1993
- Rate-constrained picture-adaptive quantization for JPEG baseline codersPublished by Institute of Electrical and Electronics Engineers (IEEE) ,1993
- Vector Quantization and Signal CompressionPublished by Springer Nature ,1992
- Optimal pruning with applications to tree-structured source coding and modelingIEEE Transactions on Information Theory, 1989
- Least squares quantization in PCMIEEE Transactions on Information Theory, 1982
- An Algorithm for Vector Quantizer DesignIEEE Transactions on Communications, 1980
- Quantizing for minimum distortionIEEE Transactions on Information Theory, 1960