Makowski, Ryszard - ed. ; Zarzycki, Jan - ed.
With the aim to better preserve sharp edges and important structure features in the recovered image, this article researches an improved adaptive total variation regularization and H-1 norm fidelity based strategy for image decomposition and restoration. Computationally, for minimizing the proposed energy functional, we investigate an efficient numerical algorithm-the split Bregman method, and briefly prove its convergence. ; In addition, comparisons are also made with the classical OSV (Osher-Sole-Vese) model (Osher et al., 2003) and the TV-Gabor model (Aujol et al., 2006), in terms of the edge-preserving capability and the recovered results. Numerical experiments markedly demonstrate that our novel scheme yields significantly better outcomes in image decomposition and denoising than the existing models.
Zielona Góra: Uniwersytet Zielonogórski
AMCS, volume 24, number 2 (2014) ; kliknij tutaj, żeby przejść
Biblioteka Uniwersytetu Zielonogórskiego
2024-04-25
2024-04-25
15
https://zbc.uz.zgora.pl/repozytorium/publication/88755
Nazwa wydania | Data |
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An efficient algorithm for adaptive total variation based image decomposition and restoration | 2024-04-25 |
Prasath, V.B. Surya Korbicz, Józef - red. Uciński, Dariusz - red.
Stanimirović, Predrag Miladinović, Marko Stojanović, Igor Miljković, Sladjana Korbicz, Józef - red. Uciński, Dariusz - red.
Oh, Cheolhwan Żak, Stanisław H. Korbicz, Józef - red. Uciński, Dariusz - red.