Perceptually Motivated Automatic Color Contrast Enhancement Based on Color Constancy Estimation

We address the problem of contrast enhancement for color images. Our method to enhance images is inspired from the retinex theory. We try to estimate the illumination and separate it from the reflectance component of an image. We use denoising techniques to estimate the illumination and while doing so achieve color constancy. We enhance only the illumination component of the image. The parameters for enhancement are estimated automatically. This enhanced illumination is then multiplied with the reflectance to obtain enhanced images with better contrast. We provide validation of our color constancy approach and show performance better than state-of-the-art approaches. We also show “visually better” results while comparing our enhancement results with those from other enhancement techniques and from commercial software packages. We perform statistical analysis of our results and quantitatively show that our approach produces effective image enhancement. This is validated by ratings from human observers.