Low light very likely leads to the degradation of image quality and even
causes visual tasks' failure. Existing image enhancement technologies are prone
to over-enhancement or color distortion, and their adaptability is fairly
limited. In order to deal with these problems, we utilise the mechanism of
biological cell vibration to interpret the formation of color images. In
particular, we here propose a simple yet effective cell vibration energy (CVE)
mapping method for image enhancement. Based on a hypothetical color-formation
mechanism, our proposed method first uses cell vibration and photoreceptor
correction to determine the photon flow energy for each color channel, and then
reconstructs the color image with the maximum energy constraint of the visual
system. Photoreceptor cells can adaptively adjust the feedback from the light
intensity of the perceived environment. Based on this understanding, we here
propose a new Gamma auto-adjustment method to modify Gamma values according to
individual images. Finally, a fusion method, combining CVE and Gamma
auto-adjustment (CVE-G), is proposed to reconstruct the color image under the
constraint of lightness. Experimental results show that the proposed algorithm
is superior to six state of the art methods in avoiding over-enhancement and
color distortion, restoring the textures of dark areas and reproducing natural
colors. The source code will be released at
https://github.com/leixiaozhou/CVE-G-Resource-Base.Comment: 13 pages, 17 figure
