The DOI matches its Crossref record.
Digital pictures: representation and compression
Abstract
For thousands of years mankind has been creating pictures which attempt to portray real or imagined scenes as perceived by human vision.Cave drawings, paintings and photographs are able to stimulate the visual system and conjure up thoughts of faraway places, imagined situations or pleasant sensations.The art of motion picture creation has advanced to the point where viewers often undergo intense emotional experiences.On-thespot news coverage gives the impression of actually witnessing events as they unfold.Relatively recently, other forms of visual information have been invented which do not, in themselves, stimulate the eye.For example, voltage variations in an electrical signal, as in television, can represent in analogous fashion the brightness variations in a picture.In this form the visual information can be stored on magnetic tape or transmitted over long distances, and, at least for engineering purposes, it is often much more useful than other forms which do stimulate human vision.With the evolution of digital techniques for information processing, storage, and transmission, the need arises for digital representation of visual information, that is, the representation of images by a sequence of integer numbers (usually binary).In this form, computer processing and digital circuit techniques can be utilized which were undreamed of only a short time ago.Machine manipulation and interpretation of visual information becomes possible.Sophisticated techniques can be employed for efficient storage of images.And processing methods can be used to significantly reduce the costs of picture transmission.Many methods have evolved for representing (or coding) visual information into a stream of numbers suitable for digital processing.Some have the virtue of easy implementation, while others have special features which make them well suited for specific applications.Most of the coding
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
Cited by
A robust content based digital signature for image authentication
Schneider, M., & Chang, S.-F. (2002) · Proceedings of 3rd IEEE International Conference on Image Processing · doi:10.1109/icip.1996.560425 · Cited by 421
A survey of hybrid MC/DPCM/DCT video coding distortions
Yuen, M., & Wu, H. R. (1998) · Signal Processing · doi:10.1016/s0165-1684(98)00128-5 · Cited by 254
Review of Postprocessing Techniques for Compression Artifact Removal
Shen, M.-Y., & Kuo, C.-C. J. (1998) · Journal of Visual Communication and Image Representation · doi:10.1006/jvci.1997.0378 · Cited by 175
Metadata
- Venue
- Choice Reviews Online
- Publisher
- American Library Association
- Published
- 1988-10-01
- Volume
- 26
- Issue
- 02
- Pages
- 26-0948-26-0948
- ISSN
- 0009-4978 (ISSN-L)
- 1523-8253
- OpenAlex
- W1485575306
- Cited by
- 505
- References
- 0
- Type
- book review
- 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: Digital pictures: representation and compression. https://app.cochat.ai/papers/10.5860/choice.26-0948
- The paper
- Digital pictures: representation and compression. (1988). Choice Reviews Online. https://doi.org/10.5860/choice.26-0948
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.