Real-Color Image Denoised and Enhanced Synchronously Based on Wavelet Transform

Real color images are images with noise. The application of gray-scale image enhancement methods in the three-channel of images (R,G,B), on the one hand, increased noise, on the other hand, tended to have a color deviation, which impacted the effect of enhancement. In view of human visual system is more sensitive to lightness than hue, saturation and noise affects lightness more than a,b color channel in CIELab space. It proposed a method of image denoised and enhanced in CIELab space. In this paper, we transform a real color image from RGB space to CIELab space at first, then maintain a,b channel unchanged, decompose lightness channel into high frequency and low frequency information using wavelet transform. And then it directly compresses dynamic range of the j-scale low frequency information based on a new illumination-reflectance model ,uses new threshold function to denoise in all scale high frequency information. At last, it transforms into a real color images from CIELab space to RGB space. Experiments show that image has a good dynamic compression range and slight color deviation, which improve the visual effects and the true effects of color.