A lattice Boltzmann method for image denoising

Authors:
Qianshun Chang;Tong Yang
Affiliations:
Institute of Applied Mathematics, Academy of Mathematics and Systems Science, Chinese academy of Sciences, Beijing, China;Department of Mathematics, City University of Hong Kong, Hong Kong, China
Venue:
IEEE Transactions on Image Processing
Year:
2009

Citing 12
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Abstract

In this paper, we construct a Lattice Boltzmann scheme to simulate the well known total variation based restoration model, that is, ROF model. The advantages of the Lattice Boltzmann method include the fast computational speed and the easily implemented fully parallel algorithm. A conservative property of the LB method is discussed. The macroscopic PDE associated with the LB algorithm is derived which is just the ROF model. Moreover, the linearized stability of the method is analyzed. The numerical computations demonstrate that the LB algorithm is efficient and robust. Even though the quality of the restored images is slightly lower than those by using the ROF model, the restored images of the LB method are satisfactory. Furthermore, computational speed of the LB method is much faster than ROFmodel. In general, CPU time of the LB method for restored images is about one tenth of ROF model.