Color Image Enhancement Using Luminance Histogram Equalization and Two-Factor Saturation Control
Ying-Kang Chen, Shaou-Gang Miaou, Ying-Cheng Lin, Yiming Chen · 2018
Many image editing software packages provide automatic image enhancement functions for general public. However, we found that, part of the image enhancement functions does not work effectively. Specifically, even after an image has been enhanced in brightness, it often induces the problems in hue shifting and poor saturation. Therefore, we attempt to control the change in hue to a minimum and avoid the change of color attributes. We use histogram equalization to increase the dynamic range of luminance and render more options for saturation improvement based on the luminance change using our proposed technique called two-factor reconstruction. The proposed method provides an adjustable parameter for users to meet their color satisfaction. For convenience, the input image will be classified into several categories, and the parameter setting guideline for the category of that image will be provided to the users so that they can adjust the parameter to achieve the desired saturation of the output image. The experimental results show that the proposed method successfully improves the performance of image brightness and contrast under the condition of preserving hue information, and simultaneously improve human visual experience by enhancing the saturation.