The DOI matches its Crossref record; 23 of the 23 references it cites were found in a registry or an index.
Naturalness Preserved Enhancement Algorithm for Non-Uniform Illumination Images
Abstract
Image enhancement plays an important role in image processing and analysis. Among various enhancement algorithms, Retinex-based algorithms can efficiently enhance details and have been widely adopted. Since Retinex-based algorithms regard illumination removal as a default preference and fail to limit the range of reflectance, the naturalness of non-uniform illumination images cannot be effectively preserved. However, naturalness is essential for image enhancement to achieve pleasing perceptual quality. In order to preserve naturalness while enhancing details, we propose an enhancement algorithm for non-uniform illumination images. In general, this paper makes the following three major contributions. First, a lightness-order-error measure is proposed to access naturalness preservation objectively. Second, a bright-pass filter is proposed to decompose an image into reflectance and illumination, which, respectively, determine the details and the naturalness of the image. Third, we propose a bi-log transformation, which is utilized to map the illumination to make a balance between details and naturalness. Experimental results demonstrate that the proposed algorithm can not only enhance the details but also preserve the naturalness for non-uniform illumination images.
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Cites
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A multiscale retinex for bridging the gap between color images and the human observation of scenes
Jobson, D. J., Rahman, Z., & Woodell, G. A. (1997) · IEEE Transactions on Image Processing · doi:10.1109/83.597272 · Cited by 3,036
Properties and performance of a center/surround retinex
Jobson, D. J., Rahman, Z., & Woodell, G. A. (1997) · IEEE Transactions on Image Processing · doi:10.1109/83.557356 · Cited by 2,330
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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
A Histogram Modification Framework and Its Application for Image Contrast Enhancement
Arici, T., Dikbas, S., & Altunbasak, Y. (2009) · IEEE Transactions on Image Processing · doi:10.1109/tip.2009.2021548 · Cited by 943
Handbook of Image and Video Processing
Wells, P. N. T. (2001) · Physiological Measurement · doi:10.1088/0967-3334/22/1/702 · Cited by 827
Multi-scale retinex for color image enhancement
Rahman, Z., Jobson, D. J., & Woodell, G. A. (2002) · Proceedings - International Conference on Image Processing · doi:10.1109/icip.1996.560995 · Cited by 803
Image 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
BLIND CONTRAST ENHANCEMENT ASSESSMENT BY GRADIENT RATIOING AT VISIBLE EDGES
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Cited by
LIME: Low-Light Image Enhancement via Illumination Map Estimation
Guo, X., Li, Y., & Ling, H. (2017) · IEEE Transactions on Image Processing · doi:10.1109/tip.2016.2639450 · Cited by 2,998
EnlightenGAN: Deep Light Enhancement Without Paired Supervision
Jiang, Y., Gong, X., Liu, D., Cheng, Y., Fang, C., Shen, X., Yang, J., Zhou, P., & Wang, Z. (2021) · IEEE Transactions on Image Processing · doi:10.1109/tip.2021.3051462 · Cited by 2,715
Kindling the Darkness: A Practical Low-light Image Enhancer
Zhang, Y., Zhang, J., & Guo, X. (2019) · Proceedings of the 27th ACM International Conference on Multimedia · doi:10.1145/3343031.3350926 · Cited by 1,507
Structure-Revealing Low-Light Image Enhancement Via Robust Retinex Model
Li, M., Liu, J., Yang, W., Sun, X., & Guo, Z. (2018) · IEEE Transactions on Image Processing · doi:10.1109/tip.2018.2810539 · Cited by 1,245
A Weighted Variational Model for Simultaneous Reflectance and Illumination Estimation
Fu, X., Zeng, D., Huang, Y., Zhang, X.-P., & Ding, X. (2016) · 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2016.304 · Cited by 1,081
Metadata
- Authors
- Wang, S., Zheng, J., Hu, H.-M., & Li, B.
- Venue
- IEEE Transactions on Image Processing
- Published
- 2013-09
- Volume
- 22
- Issue
- 9
- Pages
- 3538-3548
- ISSN
- 1057-7149 (ISSN-L)
- 1941-0042
- OpenAlex
- W2054814429
- Cited by
- 1,755
- References
- 23
- FWCI
- 17.84
- Type
- journal article
- Language
- en
- Open access
- closed
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