TY - JOUR
T1 - An Adaptive Strategy for the Restoration of Textured Images Using Fractional Order Regularization
AU - R. H. Chan, A. Lanza, S. Morigi & F. Sgallari
JO - Numerical Mathematics: Theory, Methods and Applications
VL - 1
SP - 276
EP - 296
PY - 2013
DA - 2013/06
SN - 6
DO - http://doi.org/10.4208/nmtma.2013.mssvm15
UR - https://global-sci.org/intro/article_detail/nmtma/5904.html
KW - Ill-posed problem, deblurring, fractional order derivatives, regularizing iterative
method.
AB - <p style="text-align: justify;">Total variation regularization has good performance in noise removal and edge
preservation but lacks in texture restoration. Here we present a texture-preserving
strategy to restore images contaminated by blur and noise. According to a texture
detection strategy, &nbsp;we apply spatially adaptive fractional order diffusion. A fast
algorithm based on the half-quadratic technique is used to minimize the resulting
objective function. Numerical results show the effectiveness of our strategy.</p>