The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Contrast enhancement technique based on local detection of edges
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
Edge and Curve Detection for Visual Scene Analysis
Rosenfeld, A., & Thurston, M. (1971) · IEEE Transactions on Computers · doi:10.1109/t-c.1971.223290 · Cited by 781
Feature enhancement of film mammograms using fixed and adaptive neighborhoods
Gordon, R., & Rangayyan, R. M. (1984) · Applied Optics · doi:10.1364/ao.23.000560 · Cited by 193
Cited by
Efficient Contrast Enhancement Using Adaptive Gamma Correction With Weighting Distribution
Huang, S.-C., Cheng, F.-C., & Chiu, Y.-S. (2013) · IEEE Transactions on Image Processing · doi:10.1109/tip.2012.2226047 · Cited by 1,233
Transform coefficient histogram-based image enhancement algorithms using contrast entropy
Agaian, S. S., Silver, B., & Panetta, K. A. (2007) · IEEE Transactions on Image Processing · doi:10.1109/tip.2006.888338 · Cited by 575
Transform-based image enhancement algorithms with performance measure
Agaian, S. S., Panetta, K., & Grigoryan, A. M. (2001) · IEEE Transactions on Image Processing · doi:10.1109/83.908502 · Cited by 411
Region-based contrast enhancement of mammograms
Morrow, W. M., Paranjape, R. B., Rangayyan, R. M., & Desautels, J. E. L. (1992) · IEEE Transactions on Medical Imaging · doi:10.1109/42.158944 · Cited by 337
A New Low-Light Image Enhancement Algorithm Using Camera Response Model
Ying, Z., Li, G., Ren, Y., Wang, R., & Wang, W. (2017) · 2017 IEEE International Conference on Computer Vision Workshops (ICCVW) · doi:10.1109/iccvw.2017.356 · Cited by 313
Metadata
- Authors
- Beghdadi, A., & Le Negrate, A.
- Venue
- Computer Vision, Graphics, and Image Processing
- Publisher
- Elsevier BV
- Published
- 1989-05
- Volume
- 46
- Issue
- 2
- Pages
- 162-174
- ISSN
- 0734-189X (ISSN-L)
- OpenAlex
- W2030120195
- Cited by
- 368
- References
- 2
- FWCI
- 4.37
- 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: Contrast enhancement technique based on local detection of edges. https://app.cochat.ai/papers/10.1016/0734-189x(89)90166-7
- The paper
- Beghdadi, A., & Le Negrate, A. (1989). Contrast enhancement technique based on local detection of edges. Computer Vision, Graphics, and Image Processing. https://doi.org/10.1016/0734-189x(89)90166-7
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.