The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
A Histogram Modification Framework and Its Application for Image Contrast Enhancement
Abstract
A general framework based on histogram equalization for image contrast enhancement is presented. In this framework, contrast enhancement is posed as an optimization problem that minimizes a cost function. Histogram equalization is an effective technique for contrast enhancement. However, a conventional histogram equalization (HE) usually results in excessive contrast enhancement, which in turn gives the processed image an unnatural look and creates visual artifacts. By introducing specifically designed penalty terms, the level of contrast enhancement can be adjusted; noise robustness, white/black stretching and mean-brightness preservation may easily be incorporated into the optimization. Analytic solutions for some of the important criteria are presented. Finally, a low-complexity algorithm for contrast enhancement is presented, and its performance is demonstrated against a recently proposed method.
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Cites
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
Cited by
Image Contrast and Color Enhancement Using Adaptive Gamma Correction and Histogram Equalization
Veluchamy, M., & Subramani, B. (2019) · Optik · doi:10.1016/j.ijleo.2019.02.054 · Cited by 169
Multi-region Nonuniform Brightness Correction Algorithm Based on L-Channel Gamma Transform
Qi, M., Cui, S., Chang, X., Xu, Y., Meng, H., Wang, Y., & Yin, T. (2022) · Security and Communication Networks · doi:10.1155/2022/2675950 · Cited by 72
RetractedA new method for judging thermal image quality with applications
Agaian, S., Ayunts, H., Trongtirakul, T., & Hovhannisyan, S. (2025) · Signal Processing · doi:10.1016/j.sigpro.2024.109769 · Cited by 11
Real-time bio-inspired contrast enhancement on GPU
Ureña, R., Morillas, C., & Pelayo, F. J. (2013) · Neurocomputing · doi:10.1016/j.neucom.2012.09.035 · Cited by 9
Metadata
- Authors
- Arici, T., Dikbas, S., & Altunbasak, Y.
- Venue
- IEEE Transactions on Image Processing
- Published
- 2009-09
- Volume
- 18
- Issue
- 9
- Pages
- 1921-1935
- ISSN
- 1057-7149 (ISSN-L)
- 1941-0042
- OpenAlex
- W2141704978
- Cited by
- 943
- References
- 1
- FWCI
- 32.25
- Type
- journal article
- Language
- en
- Open access
- closed
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- Arici, T., Dikbas, S., & Altunbasak, Y. (2009). A Histogram Modification Framework and Its Application for Image Contrast Enhancement. IEEE Transactions on Image Processing. https://doi.org/10.1109/tip.2009.2021548
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