Autor:

Liu, Xinwu ; Huang, Lihong

Współtwórca:

Makowski, Ryszard - ed. ; Zarzycki, Jan - ed.

Tytuł:

An efficient algorithm for adaptive total variation based image decomposition and restoration

Podtytuł:

.

Tytuł publikacji grupowej:

AMCS, Volume 24 (2014)

Temat i słowa kluczowe:

image decomposition ; image restoration ; adaptive total variation ; H-1 norm ; split Bregman method

Abstract:

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.

Wydawca:

Zielona Góra: Uniwersytet Zielonogórski

Data wydania:

2014

Typ zasobu:

artykuł

DOI:

10.2478/amcs-2014-0031

Strony:

405-415

Źródło:

AMCS, volume 24, number 2 (2014) ; kliknij tutaj, żeby przejść

Jezyk:

eng

Licencja CC BY 4.0:

kliknij tutaj, żeby przejść

Prawa do dysponowania publikacją:

Biblioteka Uniwersytetu Zielonogórskiego