| Abstract: | In this paper, we propose a generalized penalization technique and a convex
constraint minimization approach for the $p$-harmonic flow problem following the ideas in Kang & March,
IEEE T. Image Process., 16 (2007), 2251-2261]. We use fast
algorithms to solve the subproblems, such as the dual projection methods, primal-dual
methods and augmented Lagrangian methods. With a special penalization term,
some special algorithms are presented.
Numerical experiments are given to demonstrate the performance of the proposed
methods. We successfully show that our algorithms are effective and efficient due
to two reasons: the solver for subproblem is fast in essence and there is no need to solve the
subproblem accurately (even 2 inner iterations of the subproblem are enough).
It is also observed that better PSNR values are produced using the new algorithms. |
