Scale-based image enhancement using modified anisotropic diffusion filter
Scale-based image enhancement using modified anisotropic diffusion filter
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DOI：
10.1117/1.1778730
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发表时间：
2004-09
影响因子：
1.3
通讯作者：
Young-Chul Song;Doo-Hyun Choi
中科院分区：
文献类型：
--
作者：
Young-Chul Song;Doo-Hyun Choi
提出了一种基于尺度的图像增强方法，该方法利用了传感器噪声估计和基于最小可靠尺度的尺度空间方法。根据局部梯度和临界值函数之间的关系，将图像划分为代表区域复杂性的不同尺度。然后根据每个区域的复杂性调整增强程度。与现有的线性反锐化掩模、自适应反锐化掩模和基于翘曲的方法相比，该算法在均匀区域产生的噪声放大可以忽略不计，并且具有更好的边缘增强效果。
We propose a scale-based image enhancement method using a modified anisotropic diffusion filter that employs sensor noise estimation and scale space methods based on a minimum reliable scale. Based on the relationship between the local gradient and the critical value function, an image is classified into various scales representing the region's complexity. The degree of enhancement is then adjusted according to each region's complexity. When compared to the existing linear unsharp masking, adaptive unsharp masking, and warping-based methods, the proposed algorithm produces negligible noise amplification in homogeneous regions and superior edge enhancement.