The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Adaptive Coding of Monochrome and Color Images
Abstract
An efficient adaptive encoding technique using a new implementation of the Fast Discrete Cosine Transform (FDCT) for bandwidth compression of monochrome and color images is described. Practical system application is attained by maintaining a balance between complexity of implementation and performance. FDCT sub-blocks are sorted into four classes according to level of image activity, measured by the total ac energy within each sub-block. Adaptivity is provided by distributing bits between classes, favoring higher levels of activity over lower levels. Excellent performance is demonstrated in terms of mean square error and direct comparison of original and reconstructed images. Results are presented for both noiseless and noisy transmission at a total rate of 1 bit and 0.5 bit per pixel for a monochrome image and for a total rate of 2 bits and 1 bit per pixel for a color image. In every case the total bit rate includes all overhead required for image reconstruction and bit protection.
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
Ahmed, N., Natarajan, T., & Rao, K. R. (1974) · IEEE Transactions on Computers · doi:10.1109/t-c.1974.223784 · Cited by 5,156
Cited by
Woods, J., & O'Neil, S. (1986) · IEEE Transactions on Acoustics, Speech, and Signal Processing · doi:10.1109/tassp.1986.1164962 · Cited by 1,016
Image data compression: A review
Jain, A. K. (1981) · Proceedings of the IEEE · doi:10.1109/proc.1981.11971 · Cited by 709
Netravali, A. N., & Limb, J. O. (1980) · Proceedings of the IEEE · doi:10.1109/proc.1980.11647 · Cited by 451
Chen, W.-H., & Pratt, W. (1984) · IEEE Transactions on Communications · doi:10.1109/tcom.1984.1096066 · Cited by 347
Self-citation
Metadata
- Authors
- Chen, W.-H., & Smith, C.
- Venue
- IEEE Transactions on Communications
- Published
- 1977-11
- Volume
- 25
- Issue
- 11
- Pages
- 1285-1292
- ISSN
- 0096-2244 (ISSN-L)
- OpenAlex
- W2118274709
- Cited by
- 378
- References
- 1
- FWCI
- 6.00
- 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: Adaptive Coding of Monochrome and Color Images. https://app.cochat.ai/papers/10.1109/tcom.1977.1093763
- The paper
- Chen, W.-H., & Smith, C. (1977). Adaptive Coding of Monochrome and Color Images. IEEE Transactions on Communications. https://doi.org/10.1109/tcom.1977.1093763
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.
