全变差去噪
计算
降噪
图像去噪
正规化(语言学)
算法
二次方程
图像(数学)
能量泛函
摄动(天文学)
变化(天文学)
计算机科学
数学
方案(数学)
数学优化
人工智能
物理
天体物理学
数学分析
几何学
量子力学
作者
Xingwu Liu,Lihong Huang
标识
DOI:10.1016/j.matcom.2013.10.001
摘要
The staircasing effect inevitably emerges in the recovered image via the local total variation (TV) based methods. To overcome this drawback, this paper elaborates on a novel nonlocal TV scheme associated with the quadratic perturbation of the ROF model for noise removal. Computationally, we present an improved split Bregman algorithm for minimizing the proposed energy functional recursively. Experimental results clearly demonstrate that our proposed strategy outperforms the corresponding TV scheme, especially in possessing higher computation speed and preserving the textures and fine details better when image denoising.
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