Region-based adaptive anisotropic diffusion for image enhancement and denoising
Region-based adaptive anisotropic diffusion for image enhancement and denoising
复制标题
用于图像增强和去噪的基于区域的自适应各向异性扩散
DOI：
10.1117/1.3517741
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发表时间：
2010-11
影响因子：
1.3
通讯作者：
Shen, Huanfeng
中科院分区：
文献类型：
--
作者：
Wang, Yi;Niu, Ruiqing;Zhang, Liangpei;Shen, Huanfeng
提出了一种新的基于区域的自适应各向异性扩散（RAAD）图像增强和去噪方法。该算法的主要思想是进行基于区域的自适应分割。为此，我们使用每个像素的结构张量的特征值差将图像分类为均匀的细节和边缘区域。根据区域类型的不同，在各向异性扩散偏微分方程中引入可变权值，以协调前向扩散和后向扩散，从而使算法能够自适应地在均匀区域进行强平滑，在细节和边缘区域进行适当的锐化。此外，我们提出了一种自适应梯度阈值选择策略。我们建议，最佳梯度阈值应估计为均匀区域上的局部强度差的平均值。此外，我们修改了各向异性锡永离散格式，考虑到边缘方向。我们相信我们的算法是一个新的机制，图像增强和去噪。定性实验，各种一般的数字图像和几个T1和T2加权磁共振模拟图像的基础上，显示显着的改善时，RAAD算法与现有的各向异性扩散和以前的前向和后向扩散算法用于增强边缘特征，提高图像对比度。基于峰值信噪比、通用图像质量指标和结构相似性的定量分析证实了该算法的优越性。C 2010年摄影光学仪器学会
A novel region-based adaptive anisotropic diffusion (RAAD) is presented for image enhancement and denoising. The main idea of this algorithm is to perform the region-based adaptive segmentation. To this end, we use the eigenvalue difference of the structure tensor of each pixel to classify an image into homogeneous detail, and edge regions. Ac- cording to the different types of regions, a variable weight is incorporated into the anisotropic diffusion partial differential equation for compromising the forward and backward diffusion, so that our algorithm can adaptively encourage strong smoothing in homogeneous regions and suitable sharp- ening in detail and edge regions. Furthermore, we present an adaptive gradient threshold selection strategy. We suggest that the optimal gradient threshold should be estimated as the mean of local intensity differences on the homogeneous regions. In addition, we modify the anisotropic diffu- sion discrete scheme by taking into account edge orientations. We believe our algorithm to be a novel mechanism for image enhancement and de- noising. Qualitative experiments, based on various general digital images and several T1- and T2-weighted magnetic resonance simulated images, show significant improvements when the RAAD algorithm is used versus the existing anisotropic diffusion and the previous forward and backward diffusion algorithms for enhancing edge features and improving image contrast. Quantitative analyses, based on peak signal-to-noise ratio, the universal image quality index, and the structural similarity confirm the su- periority of the proposed algorithm. C 2010 Society of Photo-Optical Instrumentation
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影响因子：
2.9
作者：
ALVAREZ, L;MAZORRA, L
通讯作者：
MAZORRA, L
影响因子：
1.3
作者：
Young-Chul Song;Doo-Hyun Choi
通讯作者：
Young-Chul Song;Doo-Hyun Choi
DOI：
10.1109/78.839984
发表时间：
2000-05
期刊：
IEEE Trans. Signal Process.
影响因子：
--
作者：
Scott T. Acton
通讯作者：
Scott T. Acton
影响因子：
10.6
作者：
Gilboa, G;Sochen, N;Zeevi, YY
通讯作者：
Zeevi, YY
影响因子：
1.3
作者：
K. Choi;Yong‐Duck Chung;J. Sim;J. Moon;Hyun-Kyu Yu;Hyo-Hoon Park;Jeha Kim
通讯作者：
K. Choi;Yong‐Duck Chung;J. Sim;J. Moon;Hyun-Kyu Yu;Hyo-Hoon Park;Jeha Kim