The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
Brightness preserving dynamic fuzzy histogram equalization
Abstract
This paper proposes a novel modification of the brightness preserving dynamic histogram equalization technique to improve its brightness preserving and contrast enhancement abilities while reducing its computational complexity. The modified technique, called Brightness Preserving Dynamic Fuzzy Histogram Equalization (BPDFHE), uses fuzzy statistics of digital images for their representation and processing. Representation and processing of images in the fuzzy domain enables the technique to handle the inexactness of gray level values in a better way, resulting in improved performance. Execution time is dependent on image size and nature of the histogram, however experimental results show it to be faster as compared to the techniques compared here. The performance analysis of the BPDFHE along with that for BPDHE has been given for comparative evaluation.
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Citations
Cites
A universal image quality index
Wang, Z., & Bovik, A. C. (2002) · IEEE Signal Processing Letters · doi:10.1109/97.995823 · Cited by 5,757
Digital Image Processing: PIKS Inside
Pratt, W. K. (2002) · Wiley eBooks · doi:10.1002/0471221325 · Cited by 4,340
Contrast enhancement using brightness preserving bi-histogram equalization
Kim, Y.-T. (1997) · IEEE Transactions on Consumer Electronics · doi:10.1109/30.580378 · Cited by 1,586
A Dynamic Histogram Equalization for Image Contrast Enhancement
Abdullah-Al-Wadud, M., Kabir, M., Akber Dewan, M., & Chae, O. (2007) · IEEE Transactions on Consumer Electronics · doi:10.1109/tce.2007.381734 · Cited by 1,346
Minimum mean brightness error bi-histogram equalization in contrast enhancement
Chen, S.-D., & Ramli, A. R. (2003) · IEEE Transactions on Consumer Electronics · doi:10.1109/tce.2003.1261234 · Cited by 994
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
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
FPGA Implementation of a Fuzzy Rule Based Contrast Enhancement System for Real Time Applications
Liviu, T. (2018) · 2018 22nd International Conference on System Theory, Control and Computing (ICSTCC) · doi:10.1109/icstcc.2018.8540721 · Cited by 4
Metadata
- Authors
- Sheet, D., Garud, H., Suveer, A., Mahadevappa, M., & Chatterjee, J.
- Venue
- IEEE Transactions on Consumer Electronics
- Published
- 2010-11
- Volume
- 56
- Issue
- 4
- Pages
- 2475-2480
- ISSN
- 0098-3063 (ISSN-L)
- OpenAlex
- W2146907897
- Cited by
- 384
- References
- 6
- FWCI
- 9.95
- Type
- journal article
- Language
- en
- Open access
- closed
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- Sheet, D., Garud, H., Suveer, A., Mahadevappa, M., & Chatterjee, J. (2010). Brightness preserving dynamic fuzzy histogram equalization. IEEE Transactions on Consumer Electronics. https://doi.org/10.1109/tce.2010.5681130
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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.
