Acceleration methods for image restoration problem with different boundary conditions

Authors:
Yuying Shi;Qianshun Chang
Affiliations:
Department of Mathematics and Physics, North China Electric Power University, Beijing 102206, China;Institute of Applied Mathematics, Academy of Mathematics and System Sciences, Beijing 100080, China
Venue:
Applied Numerical Mathematics
Year:
2008

Citing 13
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An Adaptive Method for Recovering Image from Mixed Noisy Data

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Abstract

In this paper, we propose a new (mean) boundary conditions (BCs) for the total variation-based image restoration problem. We present a proof of the convergence of our difference schemes. An algebraic multigrid method and Krylov subspace acceleration are used when we solve the corresponding linear equations. The results from our new BCs are compared with the results from the other BCs introduced by several image researchers by simple and significant 2D numerical experiments. Experimental results demonstrate that our new BCs can get better restored images than the existing BCs.