搜索资源列表
PCA.rar
- 用主成分分析法提取人脸图像特征的程序，算法理论依据是K-L变换,Principal Component Analysis with face image feature extraction process
icafsvm.rar
- 用于人脸识别的模糊独立成分分析+主成分分析，用模糊支持向量机进行的分类。,Fuzzy Face Recognition for independent component analysis+ principal component analysis, using fuzzy support vector machine classification.
FastICA_25
- 独立分量分析的算法，用于分离出独立分量，用于图像降维，特征提取-Independent component analysis algorithms, used to separate out the independent component for the image dimensionality reduction, feature extraction
color_hist256
- 自己编写的提取RGB图像的包含256bin的一维直方图，首先把rgb图像转换为hsv图像，然后量化三个分量图像，最后提取一维直方图，可用于图像检索。-I have written extract contains RGB images 256bin one-dimensional histogram, first of all put rgb image is converted to hsv images, then quantified the three-component image,
MATLAB1
- 根据)EF 特性中的对比度敏感度， 即空间频率特性曲线，对图像进行二维多级小波分解，由分解后的各小波分量，提取各频段相应的亮 度、清晰度和相关度指标；然后将这三个指标的几何平均与频段加权系数的内积做算术平均，以此作 为图像质量的综合评价指标-According to) EF characteristic of contrast sensitivity, that is spatial frequency characteristic curve, the image is two-d
MPCA
- 高维PCA 参考文献： MPCA Multilinear Principal Component Analysis of Tensor Objects-High-dimensional PCA References: MPCA Multilinear Principal Component Analysis of Tensor Objects
AMulti-sourceImagFusionAlgorithmUsingICA
- 一种基于ICA的多源图像融合算法为了尽可能 达到这一要求，在分析盲源分离理论的基础上，提出了一种基于独立分量分析(ICA)的图像融合算法。-ICA-based multi-source image fusion algorithm in order to meet this requirement as far as possible, in the analysis of blind source separation based on the theory put forward bas
2DPCA
- 2DPCA 主成分分析法，处理图像压缩，特征提取的m代码-2DPCA principal component analysis, image compression processing, feature extraction of m code
pca
- PCA主成分分析，用于人脸识别，特征提取等-PCA principal component analysis for face recognition, feature extraction, etc.
pp
- 主元分析 (Principal Component Analysis, PCA) 又叫：Karhunen-Loeve变换 (KLT)、Hotelling变换。 假设已经从图象已经缩放为N*M大小。 m幅N*M大小的图象Xi作为n*1列向量看待-PCA (Principal Component Analysis, PCA) also known as: Karhunen-Loeve Transform (KLT), Hotelling transform.
Component-extraction
- Component-extraction.rar实现彩色图像的RGB三分量的提取，并将各个分量图像进行均衡化-Component-extraction.rar to achieve color image of RGB three-component extraction, and the various component images equalization
matlab-pca
- 这是一个主成分分析的matlab程序，非常有用。-This is a principal component analysis of matlab procedures, very useful.
FICA-matlab
- fast fixed-point algorithm -The FastICA package is a free (GPL) MATLAB program that implements the fast fixed-point algorithm for independent component analysis and projection pursuit. It features an easy-to-use graphical user interface, and a comput
chengxu
- 本程序应用了取两次阈值、基于特征的逻辑、二值形态学和相连成分的标识，确定了钢的显微图像中颗粒的边界，标识了不同的颗粒。-This procedure applies to take the two threshold values, based on characteristics of logic, binary morphology and connected component labeling, to determine the microstructure of steel grain
matlab
- ) 使用分块的主成分分析方法(PCA)对人脸图像进行压缩编码。针对PCA方法计算量大的缺点,首先把问题转化成奇异值分解(SVD)问题,然后设计了特征空间的更新算法,通过递推,简化每一步计算的计算量,达到了实时编码的要求。 4) 在Windows平台下基于Video for Windows(VFW)接口开发了人脸视频图像编码和解码的实验系统,该系统实现了图像采集、图像显示、编码、解码等功能。-) The use of sub-blocks of principal component analys
licenseplatelocation
- 一种多车牌定位方法，该方法综合利用边缘检 测、连通域分析、倾斜矫正等多种方法,解决了复杂背景中定位难的问题-A multi-plate location method, which combined with an edge detection, connected component analysis, tilt correction and other methods to solve the complex problem of difficulties in the context
bw-Noise-Reduction
- 这个函数获取二进制图像，然后根据图像中标记目标的连接性和每个连接组成的像素数量来判断是否是噪声。 -The function to get the binary image, then image tag target connectivity and the number of pixels of each connected component to determine whether it is noise.
Morphological-threshold-segmentation
- 实现形态学的阈值分割，可得到分割后的阈值图像，形态学图像，L的直方图，最大连通成分提取图像以及最后得出的结果图像。-Achieve morphological thresholding, the threshold obtained after image segmentation, image morphology, L histogram, the largest connected component extraction result image and the final image.
基于信息熵的约简MATLAB代码
- 利用matlab和ceemd进行编程求解简单的信息熵，根据求解的imf分量判断信号的情况(Using MATLAB and ceemd programming to solve simple information entropy, according to the IMF component to determine the situation of the signal)
MATLAB程序
- 快速PCA算法，用于快速提取出矩阵的主成分，主成分数量可定。(The fast PCA algorithm is used to extract the principal component of the matrix quickly, and the principal fraction can be determined.)