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Dynamical stochastic resonance for nonuniform illumination image enhancement
Zhang, Yongbin1,2; Liu, Hongjun1,3; Huang, Nan1; Wang, Zhaolu1
Source PublicationIET Image Processing
Contribution Rank1

Images taken under poor illumination conditions have low contrast and dark tones. General dark image enhancement algorithms cannot effectively enhance these images without introducing over-enhancement, detail loss, and noise amplification. In this study, a simple and fast enhancement technique of non-uniform illumination images is proposed based on dynamical stochastic resonance (DSR). The low-contrast images are enhanced through the nonlinear iteration by solving monostable Langevin equation. Iteration parameters are dynamically adjusted according to the intensity distribution of the original images, which ensure the balance of visibility and naturalness in the entire areas. A threshold is defined to automatically confirm the optimal outputs. The enhanced image is obtained by fusing the DSR result, original component, and illumination compensation component. The computational time, no-reference perceptual quality assessment, and lightness order error are measured to evaluate the performance of experimental results. The subjective and objective comparison with state-of-the-art methods shows that our method performs well to enhance the non-uniform illumination images with a low-computational complexity. © 2018, The Institution of Engineering and Technology.

KeywordImage Enhancement Image Fusion Stochastic Processes Iterative Methods Differential Equations Brightness Dynamical Stochastic Resonance Nonuniform Illumination Image Enhancement Dark Tones Low-contrast Image Enhancement Nonlinear Iteration Monostable Langevin Equation Iteration Parameters Intensity Distribution Visibility Balance Naturalness Balance Illumination Compensation Component Computational Time No-reference Perceptual Quality Assessment Lightness Order Error Low-computational Complexity
Indexed BySCI ; EI
WOS IDWOS:000451759800002
PublisherInstitution of Engineering and Technology
EI Accession Number20184906212039
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Document Type期刊论文
Corresponding AuthorLiu, Hongjun
Affiliation1.State Key Laboratory of Transient Optics and Photonics, Xi'an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi'an; 710119, China;
2.University of Chinese Academy of Sciences, Beijing; 100084, China;
3.Collaborative Innovation Center of Extreme Optics, Shanxi University, Taiyuan; 030006, China
Recommended Citation
GB/T 7714
Zhang, Yongbin,Liu, Hongjun,Huang, Nan,et al. Dynamical stochastic resonance for nonuniform illumination image enhancement[J]. IET Image Processing,2018,12(12):2147-2152.
APA Zhang, Yongbin,Liu, Hongjun,Huang, Nan,&Wang, Zhaolu.(2018).Dynamical stochastic resonance for nonuniform illumination image enhancement.IET Image Processing,12(12),2147-2152.
MLA Zhang, Yongbin,et al."Dynamical stochastic resonance for nonuniform illumination image enhancement".IET Image Processing 12.12(2018):2147-2152.
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