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fusion-pca
- 用PCA的方法，对两幅聚焦不同的图像进行融合处理，从而获得清晰图像。-using PCA, focusing on two different images for integration, thereby get a clear image.
联机数字、英文字符及汉字识别
- 3D model search engine A HYBRID METHOD FOR IMAGE PARTITION 一种基于视觉嫡的图像分割压缩方法
pca
- 此程序用来对单波段图像或者多波段图像进行主成分分析，可以对主成分个数进行手动设置-This procedure used for single-band image or multi-band images, principal component analysis, the number of principal components can be manually set
kpca
- 使用核PcA来识别图片，图片为200张测试图片，200张训练图片，包含在在压缩文件中。-To identify the use of nuclear PcA picture, pictures, for 200 test images, 200 training images, is included in the compressed file.
imageshow
- 用于图像处理的图形用户界面，可实现图像的翻转、加噪、边缘提取等功能。-For image processing graphical user interface, can be flipped images, noise, edge detection and other functions.
EigenFace
- This is a MFC program to test Principle Component Analysis (PCA) for constructing Eigenfaces. Using train images, it calculates Eigen values and Eigen vectors with sorting. Then reconstruct test images from PCA coefficients.
PCA
- This program carries out PCA analysis on a set of 6 bitmap images. The images contain objects against blank backgrounds. The eigenvalues and eigenvectors for the set of images are calculated and based on these decomposition coefficients are cal
MoAT7.1
- This paper identifies a novel feature space to address the problem of human face recognition from still images. This based on the PCA space of the features extracted by a new multiresolution analysis tool called Fast Discrete Curvelet Transfo
1
- Amir Hossein Omidvarnia用matlab编写的基于PCA的人脸识别系统和基于FLD的人脸识别系统,其中 的图像示例为Essex face database中 face94 的部分图像,文献可参考"Eigenfaces vs. Fisherfaces: Recognition using class specific linear projection."已经测试过程序可正常运行没有问题。-Amir Hossein Omidvarnia prepared using
pca
- pca进行人脸识别，首先对人脸图象进行训练，得到投影矩阵，然后再进行人脸识别-pca for face recognition, the first human face images for training, to be the projection matrix, and then to face recognition
Eigenfaces
- Eigenfaces tests for grayscale images using PCA and SVD
KECA
- Kernel Entropy Component Analysis,KECA方法的作者R. Jenssen自己写的MATLAB代码，文章发表在2010年5月的IEEE TPAMI上面-Kernel Entropy Component Analysis, by R. Jenssen, published in IEEE TPAMI 2010. We introduce kernel entropy component analysis (kernel ECA) as a new method
RunFaceRecog_vV
- This is a Simple Code for Face Recognition using PCA + LDA Approach. I hve write this code for ORL Database containing 400 images of 40 persons. I have used Eigenface Algorithm for Face Recognition. Its a Very Simple Code you can easily understand it
PCA-Code
- It is used for preprocessing of images
PCAbased-Laplacian-pyramid
- 本文阐述了基于主元分析的拉普拉斯金字塔图像融合的原理和方法:首先对原图像分别进行拉普拉斯 金字塔分解,然后分别对高频部分采用主元分析（PCA）法融合,对低频部分采用平均梯度法进行融合,最后对 拉普拉斯金字塔做反变换得到最终的融合图像。通过对可见光与红外图像的融合，以及对不同焦距图像融合 的结果分析，该算法比单纯的PCA和拉普拉斯图像融合能得到具有更多有用信息的高对比度的融合图像-In this paper, principal component analysis based on
PCA
- 这是基于VC++编写的对遥感影像分析的程序，主要是对遥感影像进行PCA变换，使得对影响分析不仅可以依托于现成软件，我们自己也可以开发-This is written in VC++ based on remote sensing image analysis program, mainly for remote sensing images PCA transform, makes impact analysis can not only rely on ready-made software,
PCA融合
- 对于两幅图像进行PCA融合，对高分辨率的灰度图像和低分辨率的彩色图像进行融合(For the two images of PCA fusion, the high resolution gray image and low resolution color image fusion)
pca
- 在许多领域的研究与应用中，往往需要对反映事物的多个变量进行大量的观测，收集大量数据以便进行分析寻找规律。多变量大样本无疑会为研究和应用提供了丰富的信息，但也在一定程度上增加了数据采集的工作量，更重要的是在多数情况下，许多变量之间可能存在相关性，从而增加了问题分析的复杂性，同时对分析带来不便。如果分别对每个指标进行分析，分析往往是孤立的，而不是综合的。盲目减少指标会损失很多信息，容易产生错误的结论。 因此需要找到一个合理的方法，在减少需要分析的指标同时，尽量减少原指标包含信息的损失，
PCA
- 用matlab自带的PCA算法对图像进行降维(Dimensionality reduction for images)
PCA-K
- 该算法主要包含PCA算法和K-Means聚类算法，用于SAR变化检测,包含数据图片。(The algorithm mainly includes PCA algorithm and K-means clustering algorithm for SAR change detection, including data images.)