Description: 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. Platform: |
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Author:丽仙 |
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Description: 利用小波变换方法进行多卫星遥感图像数据融合，分析不同长度的小波基对融合图像的影响，从信息的保持性、视觉效果及运用灵活性等方面与IHS、PCA 融合算法进行了比较，从而探讨这一新算法在遥感图像分析应用中的可行性。-Using wavelet transform methods of multi-satellite remote sensing image data fusion, analysis of different wavelet bases on the length of the impact of image fusion, from the maintenance of information, visual effects and the use of flexibility with the IHS, PCA fusion algorithm are compared in order to explore the This new algorithm in the application of remote sensing image analysis feasibility. Platform: |
Size: 65536 |
Author:lieutenant |
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Description: 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 an effective method to data from high dimensional data space transformation to the low-dimensional feature space, which can be used for data feature extraction and compression and so on. In this paper, the shape recognition system using PCA extraction of the shape of image features, can be used to satisfy the identification requirements of the input layer. In the recognition layer studied three kinds of identification methods: nearest neighbor rule, BP network and the synergetic neural network methods, have achieved a satisfactory experiment results. Platform: |
Size: 277504 |
Author:陈平 |
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Description: 它是SourceForge上的一个开源项目，使用Malib实现实时处理，CSU Face Identification Evaluation System进行人脸识别。算法包括：主成份分析(principle components analysis (PCA)),a.k.a eigenfaces算法,混合主成份分析,线性判别分析(PCA+LDA),图像差分分类器(IIDC),弹性图像匹配算法(EBGM)等等
Malic is realtime face recognition system that based on Malib and CSU Face Identification Evaluation System (csuFaceIdEval). Uses Malib library for realtime image processing and some of csuFaceIdEval for face recognition.-It is a SourceForge open source project, using real-time Malib processing, CSU Face Identification Evaluation System for Face Recognition. Algorithms include: Principal component analysis (principle components analysis (PCA)), aka eigenfaces algorithm, mixed-principal component analysis, linear discriminant analysis (PCA+ LDA), the image difference classifier (IIDC), a flexible image-matching algorithm (EBGM), etc. such as Malic is realtime face recognition system that based on Malib and CSU Face Identification Evaluation System (csuFaceIdEval). Uses Malib library for realtime image processing and some of csuFaceIdEval for face recognition. Platform: |
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Author:乔超 |
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Description: 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 matlab Face Recognition System Based on PCA and FLD-based face recognition systems, which sample the image of Essex face database for ' face94' part of images, documents may refer to " Eigenfaces vs. Fisherfaces: Recognition using class specific linear projection. " procedures have been tested there is no problem to normal operation. Platform: |
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Author:刘子木 |
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Description: 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 the Laplacian pyramid image fusion of theory and method: First, the original image, respectively Laplacian pyramid decomposition, and then were used for high-frequency part of the principal component analysis (PCA) fusion method for The average gradient method using low-frequency part of the fusion, the last of the Laplacian pyramid to do the inverse transform to get the final fused image. Through the integration of visual and infrared images, as well as the results of image fusion of different focal length of the algorithm than the simple PCA and Laplacian image fusion can get more useful information with the integration of high-contrast images Platform: |
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Author:redxuech |
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Description: 基于PCA的遥感影像融合Matlab程序，在Matlab 2011b上完美运行！-Remote sensing image fusion based on PCA Matlab, it works perfect on Matlab 2011b!
Platform: |
Size: 30720 |
Author:林忆 |
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Description: 一个基于FSVM的人脸识别程序，用PCA提取特征，进行识别，里面包含原始的人脸图像-A based on FSVM face recognition program, using PCA feature extraction, identification, which contains the original face image Platform: |
Size: 1352704 |
Author:周 脉成 |
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Description: pca人脸识别 基于代数统计的方法是使用统计学观点提取基向量，之后将人脸向量投影到基向量上，得到的投影值即为不同的人脸图像特征，这种方法利于操作，比较灵活。本次设计采用PCA方法对人脸进行降维，提取特征。
-pca face recognition based on the statistical method Generation is extracted base vectors using a statistical point of view, and then the vector of the face is projected to a base vector the projection value obtained is the type of face image feature, this method is beneficial operation more flexible . The design uses PCA dimensionality reduction, human face feature extraction. Platform: |
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Author:wady |
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Description: 几个基于pca的matlab程序。使用时直接输入图片就可以了-Based on several pca matlab program. When using direct input image can be Platform: |
Size: 4096 |
Author:高效 |
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Description: 直线阵采用切比学夫加权控制主旁瓣比，一些自适应信号处理的算法，分析了该信号的时域、频域、倒谱，循环谱等,借鉴了主成分分析算法（PCA），粒子图像分割及匹配均为自行编制的子例程。- Linear array using cut than learning laid upon the right control of the main sidelobe ratio, Some adaptive signal processing algorithms, Analysis of the signal time domain, frequency domain, cepstrum, cyclic spectrum, etc. It draws on principal component analysis algorithm (PCA), Particle image segmentation and matching subroutines themselves are prepared. Platform: |
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Author:nunhpc |
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Description: 本文档包含了对视频分类的方法论文，先提取视频中音频信息和图像信息，然后进行拼接并使用PCA进行降维处理，最后使用高斯联合模型进行学习和分类-This document contains papers on the video classification method, first extract the video audio information and image information, and then stitching using PCA dimension reduction, and finally the use of joint Gaussian model for learning and classification Platform: |
Size: 272384 |
Author:dwj |
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Description: 使用拉亚普诺夫指数的公式，图像的光流法计算的matlab程序,借鉴了主成分分析算法（PCA）。- Raya Punuo Fu index using the formula, Image optical flow calculation matlab program, It draws on principal component analysis algorithm (PCA). Platform: |
Size: 5120 |
Author:张红亮 |
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Description: 采用了小波去噪的思想，借鉴了主成分分析算法（PCA），粒子图像分割及匹配均为自行编制的子例程。- Using wavelet denoising thought, It draws on principal component analysis algorithm (PCA), Particle image segmentation and matching subroutines themselves are prepared. Platform: |
Size: 5120 |
Author:nuikoukoulao |
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Description: 本文提出了一种基于补丁的噪声电平估计算法，补丁产生的单噪声图像。一个可以很容易地估计噪声水平使用主成分分析（PCA）如果图像块的图像只包含弱特将补丁。基于补丁的噪声电平估计的挑战是如何选择弱纹理补丁从嘈杂的图像。去描述在本文中，我们提出了一个选择弱纹理补丁的补丁和基于统计的梯度单噪声图像的新算法。然后，我们估计噪声水平从选定的弱纹理补丁使用PCA。我们实验证明，所提出的噪声电平估计算法优于国家的最先进的算法。-A patch-based noise level estimation algorithm is proposed in this
paper, with patches generated a single noisy image. One can
easily estimate the noise level image patches using principal
component analysis (PCA) if the image comprises only weak tex-
tured patches. The challenge for patch-based noise level estimation
is how to weak textured patches a noisy image. As de-
scribed in this paper, we propose a novel algorithm to weak
textured patches a single noisy image based on the gradients
of the patches and their statistics. Then we estimate the noise level
the selected weak textured patches using PCA. We demonstrate
experimentally that the proposed noise level estimation algorithm
outperforms the state-of-the-art algorithm. Platform: |
Size: 963584 |
Author:陈怀兵 |
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Description: 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，以达到对所收集数据进行全面分析的目的。由于各变量间存在一定的相关关系，因此有可能用较少的综合指标分别综合存在于各变量中的各类信息。主成分分析与因子分析就属于这类降维的方法。(* pca.cpp
This program demonstrates how to use OpenCV PCA with a specified amount of variance to retain. The effect is illustrated further by using a trackbar to change the value for retained varaince.
The program takes as input a text file with each line begin the full path to an image. PCA will be performed on this list of images. The author recommends using
the first 15 faces of the AT&T face data set:
http://www.cl.cam.ac.uk/research/dtg/attarchive/facedatabase.html) Platform: |
Size: 2048 |
Author:Steven Cham
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Search - using pca on image