Color facial image denoising based on rpca and noisy pixel detection
Zhaojun Yuan, Xudong Xie, Xiaolong Ma, Kin‐Man Lam · 2013
In this paper, a novel approach for color facial-image denoising based on robust principal component analysis (RPCA) [1] in the L*a*b* color space and noisy pixel detection is proposed. Firstly, RPCA is employed for color facial-image recovery in the L*a*b* space. Then, the reconstructed image is used for noisy pixel detection. Finally, the denoised facial-image can be obtained. Experiments are conducted based on the AR database, where our proposed method is compared with several state-of-the-art image-denoising methods. Experimental results show that our method can achieve a better performance in terms of both quantitatively evaluation and visual quality.