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simfeat

于 2020-11-13 发布 文件大小:2733KB
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代码说明：

  简单特征提取算法:PCA,MNF,PLS,CCA,KPCA,KMNF,KPLS,KCCA等，用于图像的特征提取。(simple algorithm feature extraction ,for example: PCA,MNF,PLS,CCA,KPCA,KMNF,KPLS,KCCA，in order to extract the feature space of image.)

文件列表：

simfeat_toolbox
...............\Contents.m,2604,2013-05-23
...............\COPYING.txt,1432,2012-12-13
...............\documentation
...............\.............\lecture.pdf,2487015,2013-01-03
...............\gpml-matlab
...............\...........\doc





...............\...........\...\alg51.gif,60084,2006-03-07
...............\...........\...\alg52.gif,41085,2006-03-07
...............\...........\...\classification.html,34439,2006-03-26
...............\...........\...\fig2d.gif,36772,2006-03-15
...............\...........\...\fig2de1.gif,35364,2006-03-15
...............\...........\...\fig2de2.gif,42683,2006-03-15
...............\...........\...\fig2de3.gif,38483,2006-03-15
...............\...........\...\fig2dl1.gif,34059,2006-03-15
...............\...........\...\fig2dl2.gif,40431,2006-03-15
...............\...........\...\fig2dl3.gif,38375,2006-03-15
...............\...........\...\figepp.gif,17875,2006-03-10
...............\...........\...\figepp2.gif,23299,2006-03-10
...............\...........\...\figl.gif,6109,2006-03-27
...............\...........\...\figl1.gif,21386,2006-03-07
...............\...........\...\figlapp.gif,17854,2006-03-09
...............\...........\...\figlapp2.gif,25557,2006-03-09
...............\...........\...\figlf.gif,16078,2006-03-27
...............\...........\...\figlm.gif,16712,2006-03-27
...............\...........\...\index.html,3461,2007-06-26
...............\...........\...\regression.html,16598,2006-03-29
...............\...........\...\sparse-approx.html,7738,2006-03-29
...............\...........\...\style.css,77,2006-03-07
...............\...........\gpml
...............\...........\....\approxEP.m,5097,2007-07-24
...............\...........\....\approximations.m,1936,2007-06-27
...............\...........\....\approxLA.m,3094,2007-06-26
...............\...........\....\binaryEPGP.m,2671,2007-06-26
...............\...........\....\binaryGP.m,6941,2007-06-27
...............\...........\....\binaryLaplaceGP.m,3071,2007-06-26
...............\...........\....\Contents.m,2656,2007-06-26
...............\...........\....\htm" target=_blank>Copyright,776,2007-06-26
...............\...........\....\covConst.m,774,2007-07-24
...............\...........\....\covFunctions.m,4136,2006-05-15
...............\...........\....\covLINard.m,1046,2006-03-27
...............\...........\....\covLINone.m,984,2006-03-27
...............\...........\....\covMatern3iso.m,1392,2007-06-26
...............\...........\....\covMatern5iso.m,1417,2007-06-26
...............\...........\....\covNNone.m,2060,2007-06-26
...............\...........\....\covNoise.m,1065,2006-03-24
...............\...........\....\covPeriodic.m,1085,2006-04-07
...............\...........\....\covProd.m,2582,2006-04-07
...............\...........\....\covRQard.m,1811,2007-06-26
...............\...........\....\covRQiso.m,1647,2007-06-26
...............\...........\....\covSEard.m,1713,2007-06-26
...............\...........\....\covSEiso.m,1349,2007-06-27
...............\...........\....\covSum.m,2400,2006-03-21
...............\...........\....\cumGauss.m,3383,2007-06-26
...............\...........\....\gauher.m,2235,2007-07-24
...............\...........\....\gpr.m,2811,2010-06-23
...............\...........\....\gprSRPP.m,2963,2006-03-30
...............\...........\....\likelihoods.m,1222,2007-06-26
...............\...........\....\logistic.m,4453,2007-07-25
...............\...........\....\Makefile,131,2006-03-29
...............\...........\....\minimize.m,8997,2009-06-03
...............\...........\....\solve_chol.c,1236,2006-03-13
...............\...........\....\solve_chol.m,991,2006-03-13
...............\...........\....\sq_dist.c,1931,2006-03-13
...............\...........\....\sq_dist.m,2186,2006-03-13
...............\...........\gpml-demo
...............\...........\.........\Contents.m,791,2006-03-27
...............\...........\.........\data_6darm.mat,22768,2006-03-13
...............\...........\.........\data_boston.mat,57040,2006-03-29
...............\...........\.........\demo_ep_2d.m,7012,2006-03-29
...............\...........\.........\demo_ep_usps.m,6130,2006-03-29
...............\...........\.........\demo_gparm.m,8178,2006-03-29
...............\...........\.........\demo_gpr.m,9382,2006-03-29
...............\...........\.........\demo_gprsparse.m,6511,2006-03-29
...............\...........\.........\demo_laplace_2d.m,7257,2006-03-29
...............\...........\.........\demo_laplace_usps.m,6134,2006-03-29
...............\...........\htm" target=_blank>README,6291,2007-07-25
...............\methods
...............\.......\cca.m,1344,2012-12-28
...............\.......\cca2.m,1579,2012-12-21
...............\.......\dualpls.m,2187,2012-12-28
...............\.......\kcca.m,1643,2012-12-28
...............\.......\keca.m,1157,2013-05-23
...............\.......\kmnf.m,994,2012-12-21
...............\.......\kopls.m,958,2012-12-27
...............\.......\kpca.m,831,2012-12-21
...............\.......\kpls.m,958,2012-12-27
...............\.......\mnf.m,611,2012-12-21
...............\.......\opls.m,715,2012-12-27
...............\.......\pca.m,535,2013-05-23
...............\.......\pls.m,1930,2013-05-23
...............\.......\plsSB.m,732,2012-12-28
...............\README.txt,5243,2012-12-13
...............\simfeat.m,10392,2013-05-23
...............\tools

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  • Itxxhm
    图像细化注意，本程序的细化算法要应用于于含线条的黑白二值图像才可以看出细化效果。 (The thinning Note refinement algorithm of this program is to be applied to black and white binary image containing lines can be seen that the refinement effect.)
    2012-08-05 18:16:42下载
    积分：1
  • bitMAP_read&save
    说明：  bitMAP文件格式的图像的读取、与保存的算法，可以作为图像处理的系统的前道，非常实用。(bitMAP file format of the image read, and preservation of the algorithm, as image processing system of the former Road, very practical.)
    2006-05-04 20:04:28下载
    积分：1
  • 卷积特征可视化
    利用卷积神经网络进行特征提取，并将卷积特征可视化(Feature extraction using convolutional neural networks and visualization of convolution features)
    2019-03-06 12:07:28下载
    积分：1
  • Gabor小波对图像进行特征提取Gabor
    使用Gabor小波对图像进行特征提取，代码可以直接使用(Using the Gabor wavelet feature extraction, the code can be used directly)
    2010-05-29 10:31:00下载
    积分：1
  • feature
    图象经过gabor小波滤波。gabor小波与图像卷积。(Image after wavelet filtering gabor. gabor wavelet and image deconvolution.)
    2008-01-16 20:15:53下载
    积分：1
  • opencv4.3
    自主选择性的查看一幅图像中的部分区域的颜色直方图：允许用户在一幅图像中选择一个矩形区域，通过按住鼠标键画一个矩形，当鼠标放开是，高亮显示矩形框，同时在另一个独立的窗口中，使用画图函数画一个图表（选定区域的颜色直方图），分别用蓝，绿，红表示选中区域中每种颜色的像素数量。(Self-selective color in an image to view a partial area of ​ ​ the histogram: Allows the user to select a rectangular area in an image by holding down the mouse button to draw a rectangle when the mouse is released, the highlighted rectangle, Meanwhile in a separate window, using the drawing functions to draw a chart (selected color histogram region), respectively, with blue, green, red indicates the number of pixels in the selected area of ​ ​ each color.)
    2014-02-13 16:18:41下载
    积分：1
  • 新建文件夹
    说明：  图像拼接的Harris 算法，精确有效，实现图像无缝拼接，多幅图片显示，谢谢，希望得到采纳(image mosaicHarris algorithm for image mosaic, accurate and effective, seamless image mosaic)
    2019-05-17 12:05:35下载
    积分：1
  • 图像空域增强处理
    说明：  思想：把原始图的直方图变换为均匀分布的形式，这样就增加了灰度值的动态 范围从而达到增强图像整体对比度的效果。其优点是能自动地增强整个 图像的对比度。 1、对灰度图像进行直方图的均衡化处理，达到图像增强的目的。 2、利用平均滤波和中值滤波对图像进行平滑滤波。 3、利用拉普拉斯运算对图像进行锐化滤波。(Idea: transform the histogram of the original image into the form of uniform distribution, so as to increase the dynamic gray value Range to enhance the overall contrast of the image. Its advantage is that it can automatically enhance the contrast of the whole image. 1. The gray image is processed by histogram equalization to achieve the purpose of image enhancement. 2. Average filter and median filter are used to smooth the image. 3. Using Laplace operation to sharpen the image.)
    2019-11-13 16:49:49下载
    积分：1
  • VMD
    VMD分解阈值去噪，进行极优模态分量的选择(VMD decomposition threshold denoising, selection of very excellent modal components.)
    2018-06-05 10:22:04下载
    积分：1
  • tuxingfenxi.zip
    实现边缘特征提取的功能有很强的特征提取功能能够边缘特征进行提取(Edge feature extraction to achieve the function of the characteristics of a strong edge feature extraction functions can be extracted)
    2009-06-17 18:07:18下载
    积分：1
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