TY - JOUR
T1 - New Hybrid Variational Recovery Model for Blurred Images with Multiplicative Noise
AU - Yiqiu Dong & Tieyong Zeng
JO - East Asian Journal on Applied Mathematics
VL - 4
SP - 263
EP - 282
PY - 2018
DA - 2018/02
SN - 3
DO - http://doi.org/10.4208/eajam.240713.120813a
UR - https://global-sci.org/intro/article_detail/eajam/10920.html
KW - Convex model, image deblurring, multiplicative noise, Split-Bregman Algorithm, total variation, variational model.
AB - <p style="text-align: justify;">A new hybrid variational model for recovering blurred images in the presence
of multiplicative noise is proposed. Inspired by previous work on multiplicative noise
removal, an I-divergence technique is used to build a strictly convex model under a
condition that ensures the uniqueness of the solution and the stability of the algorithm.
A split-Bregman algorithm is adopted to solve the constrained minimisation problem
in the new hybrid model efficiently. Numerical tests for simultaneous deblurring and
denoising of the images subject to multiplicative noise are then reported. Comparison
with other methods clearly demonstrates the good performance of our new approach.</p>