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. Therefore in view of the difference of human visual system sensitivity of the hue, saturation, luminance and image noise affecting differently on the hue, saturation, and luminance, it proposed a method of image denoised and enhanced in HSV space. In this paper, according to the result of influence of V and S by noise, we transform a real color image from RGB space to HSV space at first, then maintain hue channel unchanged, decompose v 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 Byes-estimation threshold to denoise in all scale high frequency information. Saturation channel is denoised by some formula from the relationship of S, V and R, G, B. At last, it transforms into a real color images from HSV 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.