Intensity statistics-based HSI diffusion for color photo denoising

This paper presents a new image denoising model for real color photo noise removal. Our model is implemented in the hue, saturation and intensity (HSI) space. The hue and saturation denoising are combined and implemented as a complex total variation (TV) diffusion. The intensity denoising is based on a diffusion flow to minimize a new energy functional, which is constructed with intensity component statistics. Besides the common gradient-based edge stopping functions for anisotropic diffusion, specifically for color photo denoising, we incorporate an intensity-based brightness adjusting term in the new energy, which corresponds to the noise disturbance with respect to photo intensity. In addition, we use the gradient vector flow (GVF) as the new diffusion directions for more accurate and robust denoising. Compared with previous diffusion flows only based on regular image gradients, this model provides more accurate image structure and intensity noise characterization for better denoising. Comprehensive quantitative and qualitative experiments on color photos demonstrate the improved performance of the proposed model when compared with 14 recognized approaches and 2 commercial software.