Low-light Image Enhancement Using the Cell Vibration Model
- URL: http://arxiv.org/abs/2006.02271v2
- Date: Sun, 15 May 2022 03:57:00 GMT
- Title: Low-light Image Enhancement Using the Cell Vibration Model
- Authors: Xiaozhou Lei, Zixiang Fei, Wenju Zhou, Huiyu Zhou and Minrui Fei
- Abstract summary: Low light very likely leads to the degradation of an image's quality and even causes visual task failures.
We propose a new single low-light image lightness enhancement method.
Experimental results show that the proposed algorithm is superior to nine state-of-the-art methods.
- Score: 12.400040803969501
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: 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.
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