  With the wide deployment of digital image capturing equipment, the need of
denoising to produce a crystal clear image from noisy capture environment has
become indispensable. This work presents a novel image denoising method that
can tackle both impulsive noise, such as salt and pepper noise (SAPN), and
additive white Gaussian noise (AWGN), such as hot carrier noise from CMOS
sensor, at the same time. We propose to use low-rank matrix approximation to
form the basic denoising framework, as it has the advantage of preserving the
spatial integrity of the image. To mitigate the SAPN, the original noise
corrupted image is randomly sampled to produce sampled image sets. Low-rank
matrix factorization method (LRMF) via alternating minimization denoising
method is applied to all sampled images, and the resultant images are fused
together via a wavelet fusion with hard threshold denoising. Since the sampled
image sets have independent but identical noise property, the wavelet fusion
serves as the effective mean to remove the AWGN, while the LRMF method suppress
the SAPN. Simulation results are presented which vividly show the denoised
images obtained by the proposed method can achieve crystal clear image with
strong structural integrity and showing good performance in both subjective and
objective metrics.
