  Low-contrast image enhancement is essential for high-quality image display
and other visual applications. However, it is a challenging task as the
enhancement is expected to increase the visibility of an image while
maintaining its naturalness. In this paper, the weighted histogram equalization
using the entropy of the probability density function is proposed. The
computation of the local mapping functions utilizes the relationship between
non-height bin and height bin distributions. Finally, the complete tone mapping
function is produced by concatenating local mapping functions. Computer
simulation results on the CSIQ dataset demonstrate that the proposed method
produces images with higher visibility and visual quality, which outperforms
traditional and recently proposed contrast enhancement algorithms methods in
qualitative and quantitative metrics.
