Adaptive enhancement of luminance and details in images under ambient light
Haonan Su, Cheolkon Jung, Shuyao Wang, Yuanjia Du
Abstract
Image quality of mobile displays are significantly influenced by ambient light. In the daylight condition, displayed images on mobile displays are darkly perceived by human visual system (HVS), which suffer from significant detail loss. However, only luminance enhancement seriously affects image details especially for bright regions. To overcome this problem, we propose a quadratic optimization framework which includes data term for luminance enhancement and gradient term for detail enhancement. In the data term, we provide an ambient light nonlinear intensity-transfer function for adaptive luminance enhancement depending on display properties, ambient light, and image contents. In the gradient term, Weber's law is employed for detail enhancement. Finally, we achieve both luminance and detail enhancement by solving the optimization framework. Experimental results demonstrate that the proposed method remarkably enhances the visibility of displayed images under strong ambient light.
BibTeX
@inproceedings{icassp2016_adaptiveenhancem,
title = {Adaptive enhancement of luminance and details in images under ambient light},
author = {Haonan Su and Cheolkon Jung and Shuyao Wang and Yuanjia Du},
booktitle = {ICASSP 2016},
year = {2016}
}