The DOI matches its Crossref record.
An evaluation of the effectiveness of adaptive histogram equalization for contrast enhancement
Open accessAbstract
Adaptive histogram equalization (AHE) and intensity windowing have been compared using psychophysical observer studies. Experienced radiologists were shown clinical CT (computerized tomographic) images of the chest. Into some of the images, appropriate artificial lesions were introduced; the physicians were then shown the images processed with both AHE and intensity windowing. They were asked to assess the probability that a given image contained the artificial lesion, and their accuracy was measured. The results of these experiments show that for this particular diagnostic task, there was no significant difference in the ability of the two methods to depict luminance contrast; thus, further evaluation of AHE using controlled clinical trials is indicated.
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
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
Brightness preserving histogram equalization with maximum entropy: a variational perspective
Wang, C., & Ye, Z. (2005) · IEEE Transactions on Consumer Electronics · doi:10.1109/tce.2005.1561863 · Cited by 386
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
Khandakar, A., Chowdhury, M. E. H., Reaz, M. B. I., Ali, S. H. M., Kiranyaz, S., Rahman, T., Chowdhury, M. H., Ayari, M. A., Alfkey, R., Bakar, A. A. A., et al. (2022) · Sensors · doi:10.3390/s22114249 · Cited by 74
Metadata
- Authors
- Zimmerman, J. B., Pizer, S. M., Staab, E. V., Perry, J. R., McCartney, W., & Brenton, B. C.
- Venue
- IEEE Transactions on Medical Imaging
- Published
- 1988-12
- Volume
- 7
- Issue
- 4
- Pages
- 304-312
- ISSN
- 0278-0062 (ISSN-L)
- 1558-254X
- OpenAlex
- W2136118810
- Cited by
- 352
- References
- 0
- FWCI
- 6.36
- Type
- journal article
- Language
- en
- Open access
- green
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: An evaluation of the effectiveness of adaptive histogram equalization for contrast enhancement. https://app.cochat.ai/papers/10.1109/42.14513
- The paper
- Zimmerman, J. B., Pizer, S. M., Staab, E. V., Perry, J. R., McCartney, W., & Brenton, B. C. (1988). An evaluation of the effectiveness of adaptive histogram equalization for contrast enhancement. IEEE Transactions on Medical Imaging. https://doi.org/10.1109/42.14513
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.
