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图像压缩常用方法
- 主成份分析 图像压缩常用方法，压缩包中包含两种方式，协方差矩阵方法和在线方法。,PCA common method of img compression
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
IMG_PCA
- Matlab 实现 一维 PCA 压缩解压 图像，可以设置 eigen value 数目，观看压缩结果。-Matlab to achieve one-dimensional PCA-extracting compressed images, the number of eigen value can be set to watch the results of compression.
23825772hyperspectral
- 高光谱图像的一系列处理包括了例如融合压缩pca变换等等等等的程序。-Hyperspectral image processing includes a series of transformations such as the integration of compression pca, etc., etc. procedures.
PCA_cov
- 用神经网络中的PCA算法对人脸图像进行压缩及恢复-PCA with a neural network algorithm for image compression on the face and back
dsp_project
- the code conducts the image compression of the gray scale image up to 90 using 4 algos fft wavelet pca and cosine transform-the code conducts the image compression of the gray scale image up to 90 using 4 algos fft wavelet pca and cosine transform
pca-and-wavelet-for-feature
- 结合PCA和Wavelet进行图像压缩和特征提取等方面的研究-fuse wavelet and PCA for image compression,denoise and feature extraction
face-recognitionnn
- The Principal Component Analysis (PCA) is one of the most successful techniques that have been used in image recognition and compression. PCA is a statistical method under the broad title of factor analysis. The purpose of PCA is to reduce the la
GeoBlur
- Geoblur PCA. good for video compression.
abc
- 进行pca提取，实现对于图像的压缩，有利于图像的进一步处理-To pca extract further processing for image compression, image
image-processing
- 内有操作说明： 操作说明.docx 加噪：高斯、椒盐等 去噪：小波、高斯、维纳及频域上的滤波（频率可调） 压缩：JPEG、小波、PCA、位平面、FFT、DCT 以上功能都集成在了GUI界面内-There are instructions: instructions docx plus noise: Gaussian, salt and pepper and other de-noising: wavelet, Gaussian, and Wiener filter in the
histeq
- 主成分分析算法（PCA），可用于降维，也可用于处理图像相关性问题，提取主成分，分析图像细节信息和主要成分，用于图像压缩也可以-Principal component analysis algorithm (PCA), can be used for dimensionality reduction, can also be used to process images related issues, extracted principal component analysis and main
eigenface
- 利用人脸pca进行数据压缩，形成人脸特征脸，然后用最近邻法进行人脸识别。-Face pca use data compression to form facial features face recognition and then the nearest neighbor method.
pcaimage
- 基于主成分分析的图像压缩，通过传入图像矩阵、主成分配置、子块大小来进行PCA处理，可得到压缩重构的图像矩阵、压缩比、贡献率信息-Image compression based on principal component analysis, by passing the image matrix, the main component configuration, the sub-block size to PCA processing, compression can be obtained
pca_face_rec
- 这是一个用PCA算法实现的人脸识别，解压压缩包，直接运行即可(This is a face recognition using PCA algorithm, decompression compression package, direct operation can)