Detail Preserving Low Illumination Image and Video Enhancement Algorithm Based on Dark Channel Prior

LIngli Guo, Zhenhong Jia, Jie Yang, Nikola Kasabov

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)
37 Downloads (Pure)


In low illumination situations, insufficient light in the monitoring device results in poor visibility of effective information, which cannot meet practical applications. To overcome the above problems, a detail preserving low illumination video image enhancement algorithm based on dark channel prior is proposed in this paper. First, a dark channel refinement method is proposed, which is defined by imposing a structure prior to the initial dark channel to improve the image brightness. Second, an anisotropic guided filter (AnisGF) is used to refine the transmission, which preserves the edges of the image. Finally, a detail enhancement algorithm is proposed to avoid the problem of insufficient detail in the initial enhancement image. To avoid video flicker, the next video frames are enhanced based on the brightness of the first enhanced frame. Qualitative and quantitative analysis shows that the proposed algorithm is superior to the contrast algorithm, in which the proposed algorithm ranks first in average gradient, edge intensity, contrast, and patch-based contrast quality index. It can be effectively applied to the enhancement of surveillance video images and for wider computer vision applications.
Original languageEnglish
Article number85
Pages (from-to)1-20
Number of pages20
Issue number1
Publication statusPublished (in print/issue) - 23 Dec 2021

Bibliographical note

Funding Information:
Funding: This work was supported by the National Natural Science Foundation of China (No. U1803261) and the International Science and Technology Cooperation Project of the Ministry of Education of the People’s Republic of China (No. 2016–2196).

Publisher Copyright:
© 2021 by the authors. Licensee MDPI, Basel, Switzerland.


  • Dark channel prior
  • Image detail preserving
  • Images
  • Low illumination
  • Video
  • Anisotropy
  • Image Enhancement
  • Algorithms
  • Lighting


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