搜索资源列表
CoolImage
- visual c++编写，图像主分量融合,应用加权图像融合算法-visual c preparation, image PCA integration, application-weighted image fusion algorithm
pcacode
- 程序设计步骤： 1、去均值 2、计算协方差矩阵及其特征值和特征向量 3、计算协方差矩阵的特征值大于阈值的个数 4、降序排列特征值 5、去掉较小的特征值 6、去掉较大的特征值(一般没有这一步） 7、合并选择的特征值 8、选择相应的特征值和特征向量 9、计算白化矩阵 10、提取主分量
PCA
- 主分量分析,用于高维数据降维或提取目标特征。程序精简，效率高. -Principal Component Analysis is used to make data dimensionality reduction or extract target characteristics。
Researchontheshapefeatureextractionandrecognition.
- 主分量分析(PCA ) 是统计学中分析数据的一种有效的方法, 可以将数据从高维数据空间变换到低维特征空间, 因而 可以用于数据的特征提取及压缩等方面。在该文的形状识别系统中, 用PCA 法提取图像的形状特征, 能够较好地满足识别 层的输入要求。在识别层研究了3 种识别方法: 最近邻法则、BP 网络及协同神经网络方法, 均取得了满意的实验效果。-Principal component analysis (PCA) is a statistical analysis of data in a
pca
- PCA主分量分析法的MATLAB源代码,用于图像融合中-PCA code
PCA
- PCA算法，用于用于主分量分析，挺好用的-PCA algorithm for principal component analysis used, very good use! ! ! ! ! ! ! ! !
ImagePCA
- 该类计算图像的主分量,特征值,特征向量,并且使用主分量重构.-The main components of such calculation of the image, feature values, feature vectors, and the use of principal component reconstruction.
pcapro
- 基于pca的模板匹配法，按照一定的贡献值，提取前m个主分量，用较低维数的特征来进行分类-Pca-based template matching method, in accordance with a certain contribution to the value of a principal component extraction before the m, with a lower-dimensional characteristics of the number of classif
face
- 人脸识别matlab源代码，应用主分量分析（PCA）实现了人脸识别。-Face recognition matlab source code, application of principal component analysis (PCA) to achieve a face recognition.
matlab_PCA
- 用Matlab来实现PCA，并分别求出图像在第一、二、三主分量上的投影。-Using Matlab to implement PCA, and images were obtained in the first, second and third principal component on the projection.
ImageCompress
- 利用主分量分析技术进行图像压缩，实验证明该算法具有很好的压缩比-Using principal component analysis for image compression, experimental results show that the algorithm has very good compression ratio
main
- 将样本矩阵FaceContainer进行主成分分析的整个过程封装在main函数中，参数K是主分量数目，即降维至K维。计算得出样本矩阵的低维表示LowDimFacesitting和主成分分量矩阵W。-The sample matrix FaceContainer principal component analysis of the whole process is encapsulated in the main function, the parameter K is the number o
NSCTTDPCACYCLEMODULE
- 非下采样轮廓波变换与二维主分量分析的循环模式计算-nonsubsambled contourlet transform and two dimensional principle component analysis cycle module calculation
NSCTTDPCACYCLEMODULElocal
- 非下采样轮廓波变换与二维主分量分析循环模式进行局部计算-nonsubsambled contourlet transform and two dimensional principle component analysis cycle module calculation local feature
PCA
- 主分量分析的源代码，附有简单的解释说明，主要对图像矩阵做降维处理，适用多幅图像的变化检测-Principal component analysis of the source code, a simple explanation, the main image matrix reducing dimension, suitable for image change detection
PCA
- PCA是研究如何通过少数几个主分量来解释多变量的方差- - 协方差结构, 是一种有效的特征提取方法- PCA studies how to explain the variance of multivariable- covariance structure through a few principal components and it is a kind of effective method of feature extraction
87201146CoolImage
- 对图像进行了处理，把图像分块，然后进行主分量融合，从而是图像只显示每一分块的主颜色-The image processing, the image sub-block, and then the main component fusion, which is the image display only the primary colors of each sub-block
pcannc
- 主分量分析对SAR图像目标进行特征提取，用最近临方法进行分类-Principal component analysis（PCA） of SAR image target feature extraction, classification using nearest-neighbor method
KLTrancom
- 通过KL主分量变换算法，进行遥感影像6波段主分量分析。-By KL principal component transform algorithm for remote sensing image 6 band principal component analysis.
Myzhufenliangfenxi123
- 主分量分析是一种基本的多维数据描述方法，是一种能使多维数据按照实际研究的需要更好地描述出来的变换方法。-Principal component analysis is a basic descr iption of the method of multidimensional data is a multidimensional data in accordance with the needs of the actual research to better describe the tran