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Low-light Image Enhancement Using Cell Vibration Model

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journal contribution
posted on 2022-06-13, 16:24 authored by X Lei, Z Fei, W Zhou, Huiyu Zhou, M Fei

 Low light very likely leads to the degradation of an image's quality and even causes visual task failures. Existing image enhancement technologies are prone to overenhancement, color distortion or time consumption, and their adaptability is fairly limited. Therefore, we propose a new single low-light image lightness enhancement method. First, an energy model is presented based on the analysis of membrane vibrations induced by photon stimulations. Then, based on the unique mathematical properties of the energy model and combined with the gamma correction model, a new global lightness enhancement model is proposed. Furthermore, a special relationship between image lightness and gamma intensity is found. Finally, a local fusion strategy, including segmentation, filtering and fusion, is proposed to optimize the local details of the global lightness enhancement images. Experimental results show that the proposed algorithm is superior to nine state-of-the-art methods in avoiding color distortion, restoring the textures of dark areas, reproducing natural colors and reducing time cost. The image source and code will be released at https://github.com/leixiaozhou/CDEFmethod. 

Funding

10.13039/501100013314-Higher Education Discipline Innovation Project (Grant Number: D18003)

Key Project of Science and Technology Commission of Shanghai Municipality (Grant Number: 19510750300)

10.13039/501100001809-National Natural Science Foundation of China (Grant Number: 61877065)

History

Citation

IEEE Transactions on Multimedia, 2022, https://doi.org/10.1109/TMM.2022.3175634

Author affiliation

School of Computing and Mathematical Sciences, University of Leicester

Version

  • AM (Accepted Manuscript)

Published in

IEEE Transactions on Multimedia

Publisher

Institute of Electrical and Electronics Engineers

issn

1520-9210

Copyright date

2022

Available date

2022-06-13

Language

en

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