锐化
平滑的
计算机科学
人工智能
噪音(视频)
滤波器(信号处理)
计算机视觉
自适应滤波器
图像(数学)
操作员(生物学)
中值滤波器
图像处理
算法
化学
转录因子
生物化学
抑制因子
基因
作者
Amin Kheradmand,Peyman Milanfar
标识
DOI:10.3389/fict.2015.00022
摘要
In this paper, we propose an effective data-adaptive filtering mechanism for sharpening of noisy and moderately blurred images. We establish the connection of our proposed data-adaptive filtering procedure with the classic Difference of Gaussians (DoG) operator widely used in image processing and computer graphics. Our proposed filter renders a data-adaptive and noise robust version of the classical DoG filter. We also discuss interesting special cases of our general sharpening method. Experimental results verify the effectiveness of the proposed technique for sharpening real images.
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