Multiplicative Noise Removal Using TVL1 Norm and Adaptive Penalty Parameter
Guodong Wang, Jie Xu, Zhenkuan Pan, Jinbao Yang
Multiplicative Noise Removal Using TVL1 Norm and Adaptive Penalty Parameter
Guodong Wang, Jie Xu, Zhenkuan Pan, Jinbao Yang
Abstract ：Multiplicative noise removal technology is very useful in many
applications. In this paper, we propose a new multiplicative noise
removal algorithm using TVL1 norm and adaptive penalty parameter. We
use TVL1 norm as the data term and we incorporate the modified total
variation regularization term in the objective function to deal with
multiplicative noise. The balance of fidelity term and
regularization term can be changed in different areas with different
gray value. We modify the penalty parameter using facet model and we
call it as adaptive penalty parameter. Thus in iterating procedure,
our method can change the degree of noise removal in different areas
with different noise level adaptively. The results show the
outperforming effect of our method.
Key words ：
Image Denoising
Multiplicative Noise
Variational Method
Facet Model
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2014, Vol. 11 
