图像处理中 结构张量(structure tensor) 结构张量(structure tensor) 主要用于区分图像的平坦区域、边缘区域与角点区域。 此处的张量就是一个关于图像的结构矩阵,矩阵结构构成如下: Rx,Ry分别为图像的水平与垂直梯度,而后进行求矩阵T的行列式K与迹(trace)H。 根据K与H的关系来求得区分图像的平坦、边缘与角点区域: ...
根据结构张量能区分图像的平坦区域、边缘区域与角点区域。 此算法也算是计算机科学最重要的32个算法之一了。链接的文章中此算法名称为Strukturtensor算法,不过我搜索了一下,Strukturtensor这个单词好像是德语,翻译过来就是structure tensor结构张量了。 此处所说的张量不是相对论或黎曼几何里的张量,黎曼几何的张量好多论文...
Ahmadreza Baghaie, Zeyun Yu, Structure tensor based image interpolation method, AEU - International Journal of Electronics and Communications, Volume 69, Issue 2, February 2015, Pages 515-522, ISSN 1434-8411.A. Baghaie and Z. Yu, "Structure tensor based image interpolation method," AEU-...
importnumpyasnpfromstructure_tensorimporteig_special_2d,structure_tensor_2dsigma=1.5rho=5.5# Load 2D data.image=np.random.random((128,128))S=structure_tensor_2d(image,sigma,rho)val,vec=eig_special_2d(S) For volume with shape(x, y, z)the eigenvectors (vec) are returned aszyx. ...
网络结构张量 网络释义 1. 结构张量 本文重点关注基于结构张量(structure tensor)的图像建模方法,对基于结构张量的偏微分方程(PDE)和变分泛函方法的滤波 … www.lunwenhot.com|基于7个网页 例句
A Structure Tensor is a symmetric tensor used in computer science that can be stored in a vector to preserve its components and reduce the dimension of the associated space. It is often normalized to preserve the Frobenius norm. AI generated definition based on: Handbook of Blind Source Separati...
具有结构张量 [19]–[21] 的基于梯度的方法通常将图像融合视为一个变分问题,然而,这些方法需要耗时的迭代过程来获得融合图像,并且往往会使融合图像的结构张量与输入的结构张量不同。 现有的基于卷积神经网络(CNN)的图像融合方法由于缺乏用于监督学习的标记数据,应用起来仍然具有挑战性。cnn通过传统的融合策略(如加法和...
Structure tensor is employed to extract local features in detail sub-bands. A nonlinear flow based on the trace of the structure tensor matrix is applied to matrix element before calculating the eigenvalues. The source data with larger eigenvalue contains more geometric features. An adap...
The corresponding tensor structure function $b_2(x,Q^2)$ rises towards small $x$, and we predict the about one percent tensor asymmetry $A_2(x,Q^2) =b_2(x,Q^2)/F_{2D}(x,Q^2)$. We calculate the shadowing of the gluon distribution in the deuteron for two different pomeron ...
MIT 3.60 | Lec 10a: Symmetry, Structure, Tensor Properties of Materials麻省理工学院3.60 |LEC 10A:对称性,结构,材料的张量性质 Part 1: 3D Symmetries, Point Groups View the complete course at: http://ocw.mit.edu/3-60F05 License: Creative Commons BY-NC-S