1) fractional gradient vector
分数阶梯度向量
2) gradient vector
梯度向量
1.
Firstly,wavelet detail coefficients are optimized,and the magnitude of the image gradient vector is determined by the energy of the wavelet coefficients.
该算法将修复过程分为两个步骤;首先寻找小波细节系数,用小波系数的能量来确定每一个图像梯度向量的大小;然后使用图像梯度向量来决定修复区中的哪个块应该首先被填充,使用基于小波域的纹理合成方法来具体填充这个块。
3) first-order gradient centripetal rate
一阶梯度向心率
1.
Methods:In this paper,the author detects malignant mass employing the method of average fraction under the minimum(AFUM) and the first-order gradient centripetal rate.
方法:作者利用AFUM(average fraction under the minimum)[1]算子和一阶梯度向心率估计检测肿块异常区域。
4) gradient vector flow
梯度向量流
1.
Image registration based on improved gradient vector flow and maximization of mutual information;
基于改进梯度向量流与最大互信息的图像配准
2.
An Active Contour Algorithm Based on Improved Gradient Vector Flow;
一种基于改进梯度向量流的主动轮廓算法的研究
3.
Therefore,according to features of the contours in fabric drape images,an active contour model(Snakes model)based on the gradient vector flow(GVF) field is proposed to recognize the edges of fabrics.
根据织物悬垂图像的边缘轮廓特点,提出采用基于梯度向量流场(GVF)的动态轮廓模型(Snake模型)来识别织物的边缘轮廓。
5) gradient vector flow(GVF)
梯度向量流
1.
Firstly,a representation of a given image at multiple scales was derived,by means of a smoothing method which minimized total variation norm of the image incorporated gradient vector flow(GVF).
首先使用引入梯度向量流的全变差方法对图像进行多尺度空间分析,然后使用一种改进的CV模型进行分割。
2.
In this paper,on the basis of Gradient Vector Flow(GVF) snakes,a fully automatic image segmentation algorithm based on the analysis of flow field and the minimal path method is proposed.
人工干预使蛇模型只能用于半自动的图像分割,该文在梯度向量流(GVF)蛇模型的基础上提出一种基于流场节点与最小路径方法的全自动图像分割算法。
补充资料：连分数的渐近分数
连分数的渐近分数
convergent of a continued fraction
连分数的渐近分数l阴ve吧e时ofa阴‘毗d五，比.;n侧卫xp口.坦”八卯6‘] 见连分数(con tinued fraction).
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