搜索资源列表
nuisie
- 用于图像处理的独立分量分析，是学习PCA特征提取的很好的学习资料，利用最小二乘法进行拟合多元非线性方程。- Independent component analysis for image processing, Is a good learning materials to learn PCA feature extraction, Multivariate least squares fitting method of nonlinear equations.
tingyan
- 用于图像处理的独立分量分析，Gabor小波变换与PCA的人脸识别代码，人脸识别中的光照处理方法。- Independent component analysis for image processing, Gabor wavelet transform and PCA face recognition code, Face Recognition light treatment method.
PCA
- 数据来源：ORL Database of Faces人脸数据库 其中同一个人的10张人脸图像为一组，共40组,图像大小为112x92 采用PCA算法实现对人脸的识别，当每组训练样本占70 时，识别准确率达到96.67 -Source: ORL Database of Faces face in which the same person 10 face images as a group, a total of 40 groups, image size of 112x92 using
henpui_V4.1
- 正确率可以达到98％，用于图像处理的独立分量分析，Gabor小波变换与PCA的人脸识别代码。- Accuracy can reach 98 , Independent component analysis for image processing, Gabor wavelet transform and PCA face recognition code.
naoyeng
- Gabor小波变换与PCA的人脸识别代码，这个有中文注释，看得明白，用于图像处理的独立分量分析。- Gabor wavelet transform and PCA face recognition code, The Chinese have a comment, understand it, Independent component analysis for image processing.
nuimiu_v87
- 最小二乘回归分析算法，用于图像处理的独立分量分析，借鉴了主成分分析算法（PCA）。- Least-squares regression analysis algorithm, Independent component analysis for image processing, It draws on principal component analysis algorithm (PCA).
PCA_FilterBank
- PCANet_FilterBank，基于主成分分析的卷积神经网络,其中主成分分析得到的主元作为网络映射的滤波器。-PCA was used as the filter in PCANets. It is really useful for image classification.
dq736
- 用于图像处理的独立分量分析，一个计算声子晶体结构的一维传递矩阵法,是学习PCA特征提取的很好的学习资料。- Independent component analysis for image processing, A one-dimensional transfer matrix method to calculate the phonon crystal structure, Is a good learning materials to learn PCA feature extractio
PCA_IMGCPS
- 对数字图片进行主成分分析，提取关键信息，进行图片信息的识别。-PCA for an image
PCA-SVM
- 用于主成分图像svm分类，简单，有很好的程序，适合初学者(SVM for principal component image classification, simple, there are very good procedures for beginners)
piotr_toolbox
- This toolbox is meant to facilitate the manipulation of images and video in Matlab. Its purpose is to complement, not replace, Matlab's Image Processing Toolbox, and in fact it requires that the Matlab Image Toolbox be installed. Emphasis has been pl
2dpca
- 一种改进的 pca 算法，2dpca用于识别图像。(a new technique coined two-dimensional principal component analysis (2DPCA) is developed for image representation)
PCA2
- 此代码为主成分分析，采用matlab编写，可以用于数据处理和人脸图像处理，此代码为基于pca的人脸识别。(This code is based on component analysis, written using MATLAB, can be used for data processing and face image processing, the code for PCA based face recognition)
jenyen-V4.6
- Using MATLAB dynamic clustering or iterative self-organizing data analysis, Independent component analysis for image processing, Is a good learning materials to learn PCA feature extraction.
PCA
- 高光谱遥感与传统的单波段、多光谱数据相比，波段量大量增加、波段宽度极大降低，对地面目标的光谱特性的测度更加细致，然而波段的增多必然导致数据量急剧增加、计算量增大、信息冗余增加以及统计参数的估计偏差增大。因此，对高光谱数据进行降维处理具有重要意义。一方面，降维能够使图像远离噪声，提高图像数据质量；另一方面，能够去除图像中的无价值波段，减少波段数，从而降低计算量，提高运算效率。主成分分析是常用的高光谱数据降维处理方法之一。(Compared with the single band, hypersp
xm250
- Independent component analysis for image processing, Based on matlab GUI interface design, It draws on principal component analysis algorithm (PCA).
pcadenoise
- 矩阵 pca或者低秩方法去噪，利用svd分解，实现对图像矩阵的去噪，该方法支持对rgb图像的去噪。使用代码请 文章中表明出处，感谢。 感谢重庆市研究生科研创新项目支持，项目号CYS16183(image denoise by low-rand regularizer or pca method. the low rank is evaluted by svd, and this method is also support for rgb image.)
PCA
- Matlab 平台使用2DPCA对二维图像数据进行降低图片的维度。提高图像处理速度。(The Matlab platform uses 2DPCA to reduce the dimension of the image data for two-dimensional image data. Improve the speed of image processing.)
PCA_classifier_version1b
- 许多图像问题需要某种物体的检测，其中图像之间的物体的外观有自然的变化。 如人脸识别，病变检测，神经通道分割。 这些图像问题可以通过手动注释图像对象来解决，以训练识别正常物体外观的模型。 这可以通过基于PCA的最大似然分类器来完成。(PCA algorithm suitable for detection / recognition of 2D image "objects")
人脸识别 MATLAB代码
- 使用pca方法对图像进行特征提取，对训练集的20个人的共一百张人脸进行训练，使用adaboost算法生成强分类器，可以对测试集的人脸图片进行识别，且识别率较高(The PCA method is used to extract the features of the image, and the training is carried out for a total of 100 faces of 20 people in the training set. The AdaBoost algor