Color preserving contrast enhancement for low light level images based on Retinex
In this paper, we propose a novel contrast enhancement algorithm for low light level images, which preserves image details and color constancy based on Retinex. We decompose an input low contrast image into luminance and chrominance components in Lab color space, which reflects the perception characteristics of human visual system well, and enhance the luminance component only. We first estimate illumination using adaptive bilateral filtering, which guarantees the available range of reflectance by considering proper neighboring pixels according to their luminance and color values. Then we enhance the contrast of the estimated illumination image using parabola-based tone mapping function. Finally, the enhanced luminance and the original chrominance are combined together to yield an enhanced color image. Experiment results show that the proposed algorithm enhances image details and edge structures by alleviating halo artifacts, and also preserves naturalness faithfully by avoiding color shifting artifacts.