The DOI matches its Crossref record; 17 of the 17 references it cites were found in a registry or an index.
Image enhancement using a contrast measure in the compressed domain
Abstract
An image enhancement algorithm for images compressed using the JPEG standard is presented. The algorithm is based on a contrast measure defined within the discrete cosine transform (DCT) domain. The advantages of the psychophysically motivated algorithm are 1) the algorithm does not affect the compressibility of the original image because it enhances the images in the decompression stage and 2) the approach is characterized by low computational complexity. The proposed algorithm is applicable to any DCT-based image compression standard, such as JPEG, MPEG 2, and H. 261.
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Cites
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Self-citationPeli, E. (1988) · Annual Meeting Optical Society of America · doi:10.1364/oam.1988.fd8 · Cited by 937
Self-citationImage enhancement via adaptive unsharp masking
Polesel, A., Ramponi, G., & Mathews, V. J. (2000) · IEEE Transactions on Image Processing · doi:10.1109/83.826787 · Cited by 782
Image and Video Compression Standards: Algorithms and Architectures
Bhaskaran, V., & Konstantinides, K. (2014) · CERN Document Server (European Organization for Nuclear Research) · Cited by 633
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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
Contrast enhancement technique based on local detection of edges
Beghdadi, A., & Le Negrate, A. (1989) · Computer Vision, Graphics, and Image Processing · doi:10.1016/0734-189x(89)90166-7 · Cited by 368
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
Image and Video Compression Standards
Bhaskaran, V., & Konstantinides, K. (1995) · Springer eBooks · doi:10.1007/978-1-4757-2358-8 · Cited by 248
Cited by
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
Detecting Camouflaged Object in Frequency Domain
Zhong, Y., Li, B., Tang, L., Kuang, S., Wu, S., & Ding, S. (2022) · 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr52688.2022.00446 · Cited by 317
Human visual system-based image enhancement and logarithmic contrast measure
Panetta, K. A., Wharton, E. J., & Agaian, S. S. (2008) · IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics) · doi:10.1109/tsmcb.2007.909440 · Cited by 267
Parameterized logarithmic framework for image enhancement
Panetta, K., Agaian, S., Zhou, Y., & Wharton, E. J. (2011) · IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics) · doi:10.1109/tsmcb.2010.2058847 · Cited by 143
A critical analysis on perceptual contrast and its use in visual information analysis and processing
Beghdadi, A., Qureshi, M. A., Amirshahi, S. A., Chetouani, A., & Pedersen, M. (2020) · IEEE Access · doi:10.1109/access.2020.3019350 · Cited by 31
Metadata
- Authors
- Tang, J., Peli, E., & Acton, S.
- Venue
- IEEE Signal Processing Letters
- Published
- 2003-10
- Volume
- 10
- Issue
- 10
- Pages
- 289-292
- ISSN
- 1070-9908 (ISSN-L)
- 1558-2361
- OpenAlex
- W2170551850
- Cited by
- 287
- References
- 17
- FWCI
- 8.01
- Type
- journal article
- Language
- en
- Open access
- closed
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- Tang, J., Peli, E., & Acton, S. (2003). Image enhancement using a contrast measure in the compressed domain. IEEE Signal Processing Letters. https://doi.org/10.1109/lsp.2003.817178
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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.
