图像向量 meaning in English

graphics vector

Firstly , to perform pca or lda on basis of such high - dimensional image vectors is a time - consuming process . secondly , the high dimensionality usually leads to singularity of the within - class covariance matrix , which is a trouble for calculation of fisher optimal discriminant vectors
这样就从根本上避免了在高维的图像向量空间内构造散布矩阵并计算特征向量的困难，大幅度地降低了特征抽取过程所耗费的计算量。
The conventional principal component analysis ( pca ) and fisher linear discriminant analysis ( lda ) are based on vectors . that is to say , if we use them to deal with the image recognition problem , the first step is to transform original image matrices into same dimensional vectors , and then rely on these vectors to evaluate the covariance matrix and to determine the projector
所提出的这两种方法的共同特点是，在进行图像特征抽取时，不需要事先将图像矩阵转化为高维的图像向量，而是直接利用图像矩阵本身构造图像散布矩阵，然后基于这些散布矩阵进行主分量分析与线性鉴别分析。