1) neighborhood gray difference
邻域灰度差
1.
This paper introduces an image segmentation algorithm of weighted with neighborhood gray difference fuzzy C-means clustering.
提出了邻域灰度差加权的模糊C均值聚类算法,实验结果表明,该算法不仅取得了很好的分割效果,而且加快了算法的收敛速度,从而满足了图像分割的有效性、实时性的要求。
2) difference of the gray-level
邻域灰度差值
1.
According to the analysis of the threshold method for image segmentation based on the traditional 2D gray-level histogram which partitioned the areas with some wrong pixels and processes slowly,this paper brought forword a new method which built the 2D histogram using the difference of the gray-level in the neighborhood.
针对传统二维灰度直方图的阈值分割方法中区域划分像素易丢失、运算速度慢等不足,通过深入分析图像中邻域灰度偏离的情况,并充分考虑像素的空间灰度信息,提出一种利用像素邻域灰度差值的新方法构建二维直方图;基于二维类间方差法实现了图像二维Otsu分割方法,并给出了相应算法的实现步骤。
3) The square value of neighborhood subtraction
邻域灰度平方差
4) distribution of gray level in the neighborhood
邻域灰度分布
1.
Thus a method of detecting smallmoving targets based on the distribution of gray level in the neighborhood is described.
图像中邻域内灰度起伏程度越大 ,各点灰度值占邻域内总灰度值的比率的平方和越大 ,由此提出了一种基于邻域灰度分布的弱小目标检测方法。
5) neighbor average grey
邻域平均灰度
1.
Based on global threshold, a new dynamic thresholding approach is proposed which is adjusted with th weighting of the difference between neighbor average grey and global threshold.
以全局阈值为基础,用邻域平均灰度与全局阈值之差的加权值对其进行调整,从而形成一种新的动态阈值分割法。
6) grey neighborhood
灰邻域
1.
Therefore,the concept of gery neighborhood and its border are established and the feature of the grey neighborhood border is discussed.
本文在灰距离空间的基础上,把经典微分学中邻域及其边界的概念推广到有理灰数中去,建立了灰邻域及其边界的概念,并研究了灰邻域边界的特殊性。
补充资料：超导电性的局域和非局域理论（localizedandnon-localizedtheoriesofsuperconductivity）
超导电性的局域和非局域理论（localizedandnon-localizedtheoriesofsuperconductivity）
伦敦第二个方程（见“伦敦规范”）表明，在伦敦理论中实际上假定了js(r)是正比于同一位置r的矢势A(r)，而与其他位置的A无牵连；换言之，局域的A(r)可确定该局域的js(r)，反之亦然，即理论具有局域性，所以伦敦理论是一种超导电性的局域理论。若r周围r'位置的A(r')与j(r)有牵连而影响j(r)的改变，则A(r)就为非局域性质的。由于`\nabla\timesbb{A}=\mu_0bb{H}`，所以也可以说磁场强度H是非局域性的。为此，超导电性需由非局域性理论来描绘，称超导电性的非局域理论。皮帕德非局域理论就是典型的超导电性非局域唯象理论。
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
参考词条