The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Rate-distortion methods for image and video compression
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.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
A Mathematical Theory of Communication
Shannon, C. E. (1948) · Bell System Technical Journal · doi:10.1002/j.1538-7305.1948.tb01338.x · Cited by 88,486
An Algorithm for Vector Quantizer Design
Linde, Y., Buzo, A., & Gray, R. (1980) · IEEE Transactions on Communications · doi:10.1109/tcom.1980.1094577 · Cited by 7,201
Cited by
Video coding with optimal inter/intra-mode switching for packet loss resilience
Zhang, R., Regunathan, S. L., & Rose, K. (2000) · IEEE Journal on Selected Areas in Communications · doi:10.1109/49.848250 · Cited by 631
Video Compression - From Concepts to the H.264/AVC Standard
Sullivan, G. J., & Wiegand, T. (2005) · Proceedings of the IEEE · doi:10.1109/jproc.2004.839617 · Cited by 538
Fast approximate energy minimization with label costs
Delong, A., Osokin, A., Isack, H. N., & Boykov, Y. (2010) · 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2010.5539897 · Cited by 404
Fast Approximate Energy Minimization with Label Costs
Delong, A., Osokin, A., Isack, H. N., & Boykov, Y. (2012) · International Journal of Computer Vision · doi:10.1007/s11263-011-0437-z · Cited by 381
\(\lambda \) Domain Rate Control Algorithm for High Efficiency Video Coding
Li, B., Li, H., Li, L., & Zhang, J. (2014) · IEEE Transactions on Image Processing · doi:10.1109/tip.2014.2336550 · Cited by 371
Metadata
- Authors
- Ortego, A., & Ramchandran, K.
- Venue
- IEEE Signal Processing Magazine
- Published
- 1998
- Volume
- 15
- Issue
- 6
- Pages
- 23-50
- ISSN
- 1053-5888 (ISSN-L)
- OpenAlex
- W2152486668
- Cited by
- 808
- References
- 2
- FWCI
- 25.47
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Rate-distortion methods for image and video compression. https://app.cochat.ai/papers/10.1109/79.733495
- The paper
- Ortego, A., & Ramchandran, K. (1998). Rate-distortion methods for image and video compression. IEEE Signal Processing Magazine. https://doi.org/10.1109/79.733495
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
