Blind Image Denoising Using Low Rank Matrix Minimization

This paper presents a simple approach for blind image denoising on Low Rank Matrix Minimization (LRMM). The LRMM has been shown to achieve a great success on Additive White Gaussian Noise (AWGN) image denoising. However, the LRMM requires information about noise level before performing the denoising task. This paper modifies the LRMM approach into blind denoising environment in which the noise level is directly estimated from a noisy image. Thus, the denoising process can be effectively performed. As documented in experimental section, the proposed method yields a promising result on blind image denoising.