An Adaptive Strategy for the Restoration of Textured Images using Fractional Order Regularization
An Adaptive Strategy for the Restoration of Textured Images using Fractional Order Regularization
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DOI：
10.1017/s1004897900001239
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发表时间：
2013-02
影响因子：
1.3
通讯作者：
R. Chan;A. Lanza;S. Morigi;F. Sgallari
中科院分区：
文献类型：
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作者：
R. Chan;A. Lanza;S. Morigi;F. Sgallari
全变分正则化在噪声去除和边缘保留方面具有良好的性能，但在纹理恢复方面缺乏。在这里，我们提出了一种纹理保留策略来恢复被模糊和噪声污染的图像。根据纹理检测策略，我们应用空间自适应分数阶扩散。基于半二次技术的快速算法用于最小化所得目标函数。数值结果显示了我们策略的有效性。
Total variation regularization has good performance in noise removal and edge preservation but lacks in texture restoration. Here we present a texture-preserving strategy to restore images contaminated by blur and noise. According to a texture de- tection strategy, we apply spatially adaptive fractional order diffusion. A fast algorithm based on the half-quadratic technique is used to minimize the resulting objective func- tion. Numerical results show the effectiveness of our strategy.