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ADMM-MATLAB

于 2020-11-09 发布
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代码说明：

说明：  基于ADMM的TV正则化最小化稀疏重建算法(TV Minimization Sparse Reconstruction Algorithms Based on ADMM)

文件列表：

ADMM-MATLAB\ADMM-MATLAB\TVAL3_beta2.4\TVAL3_beta2.4\demo.m, 1412 , 2010-06-17
ADMM-MATLAB\ADMM-MATLAB\TVAL3_beta2.4\TVAL3_beta2.4\Demos\demo_barbara.m, 3196 , 2010-11-10
ADMM-MATLAB\ADMM-MATLAB\TVAL3_beta2.4\TVAL3_beta2.4\Demos\demo_complex.m, 2530 , 2010-11-10
ADMM-MATLAB\ADMM-MATLAB\TVAL3_beta2.4\TVAL3_beta2.4\Demos\demo_DFT.m, 3961 , 2010-11-10
ADMM-MATLAB\ADMM-MATLAB\TVAL3_beta2.4\TVAL3_beta2.4\Demos\demo_phantom.m, 2611 , 2010-11-10
ADMM-MATLAB\ADMM-MATLAB\TVAL3_beta2.4\TVAL3_beta2.4\Fast_Walsh_Hadamard_Transform\fWHtrans.cpp, 3450 , 2010-02-16
ADMM-MATLAB\ADMM-MATLAB\TVAL3_beta2.4\TVAL3_beta2.4\Fast_Walsh_Hadamard_Transform\fWHtrans.mexa64, 8416 , 2010-04-05
ADMM-MATLAB\ADMM-MATLAB\TVAL3_beta2.4\TVAL3_beta2.4\Fast_Walsh_Hadamard_Transform\fWHtrans.mexmaci, 9284 , 2010-06-17
ADMM-MATLAB\ADMM-MATLAB\TVAL3_beta2.4\TVAL3_beta2.4\Fast_Walsh_Hadamard_Transform\fWHtrans.mexmaci64, 9112 , 2010-11-10
ADMM-MATLAB\ADMM-MATLAB\TVAL3_beta2.4\TVAL3_beta2.4\Fast_Walsh_Hadamard_Transform\fWHtrans.mexw32, 6656 , 2010-11-10
ADMM-MATLAB\ADMM-MATLAB\TVAL3_beta2.4\TVAL3_beta2.4\Fast_Walsh_Hadamard_Transform\fWHtrans.mexw64, 9216 , 2010-11-10
ADMM-MATLAB\ADMM-MATLAB\TVAL3_beta2.4\TVAL3_beta2.4\Fast_Walsh_Hadamard_Transform\ifWHtrans.m, 446 , 2010-02-15
ADMM-MATLAB\ADMM-MATLAB\TVAL3_beta2.4\TVAL3_beta2.4\Fast_Walsh_Hadamard_Transform\newFWHTcmp.fig, 11358 , 2010-02-17
ADMM-MATLAB\ADMM-MATLAB\TVAL3_beta2.4\TVAL3_beta2.4\Fast_Walsh_Hadamard_Transform\readme.txt, 2115 , 2010-06-17
ADMM-MATLAB\ADMM-MATLAB\TVAL3_beta2.4\TVAL3_beta2.4\Solver\ftvcs_alp.m, 15273 , 2010-11-10
ADMM-MATLAB\ADMM-MATLAB\TVAL3_beta2.4\TVAL3_beta2.4\Solver\ftvcs_alp_old.m, 14446 , 2010-11-10
ADMM-MATLAB\ADMM-MATLAB\TVAL3_beta2.4\TVAL3_beta2.4\Solver\ftvcs_al_opts.m, 5646 , 2010-11-10
ADMM-MATLAB\ADMM-MATLAB\TVAL3_beta2.4\TVAL3_beta2.4\Solver\ftvcs_al_TVL2p.m, 14704 , 2010-11-10
ADMM-MATLAB\ADMM-MATLAB\TVAL3_beta2.4\TVAL3_beta2.4\Solver\ftvcs_al_TVL2p_old.m, 13827 , 2010-11-10
ADMM-MATLAB\ADMM-MATLAB\TVAL3_beta2.4\TVAL3_beta2.4\Solver\readme.txt, 2834 , 2010-06-17
ADMM-MATLAB\ADMM-MATLAB\TVAL3_beta2.4\TVAL3_beta2.4\Solver\TVAL3.m, 674 , 2010-11-09
ADMM-MATLAB\ADMM-MATLAB\TVAL3_beta2.4\TVAL3_beta2.4\User_Guide.pdf, 140176 , 2010-11-10
ADMM-MATLAB\ADMM-MATLAB\TVAL3_beta2.4\TVAL3_beta2.4\Utilities\At_fWH.m, 284 , 2010-06-17
ADMM-MATLAB\ADMM-MATLAB\TVAL3_beta2.4\TVAL3_beta2.4\Utilities\A_fWH.m, 244 , 2010-06-17
ADMM-MATLAB\ADMM-MATLAB\TVAL3_beta2.4\TVAL3_beta2.4\Utilities\barbara256.tif, 107022 , 2009-06-15
ADMM-MATLAB\ADMM-MATLAB\TVAL3_beta2.4\TVAL3_beta2.4\Utilities\defDDt.m, 379 , 2009-02-19
ADMM-MATLAB\ADMM-MATLAB\TVAL3_beta2.4\TVAL3_beta2.4\Utilities\Fp1d.m, 197 , 2008-08-27
ADMM-MATLAB\ADMM-MATLAB\TVAL3_beta2.4\TVAL3_beta2.4\Utilities\Fp2d.m, 326 , 2008-11-17
ADMM-MATLAB\ADMM-MATLAB\TVAL3_beta2.4\TVAL3_beta2.4\Utilities\FpT1d.m, 233 , 2008-08-27
ADMM-MATLAB\ADMM-MATLAB\TVAL3_beta2.4\TVAL3_beta2.4\Utilities\FpT2d.m, 265 , 2008-11-17
ADMM-MATLAB\ADMM-MATLAB\TVAL3_beta2.4\TVAL3_beta2.4\Utilities\f_handleA.m, 202 , 2009-02-17
ADMM-MATLAB\ADMM-MATLAB\TVAL3_beta2.4\TVAL3_beta2.4\Utilities\getA.m, 590 , 2009-02-09
ADMM-MATLAB\ADMM-MATLAB\TVAL3_beta2.4\TVAL3_beta2.4\Utilities\isinInterval.m, 369 , 2008-06-14
ADMM-MATLAB\ADMM-MATLAB\TVAL3_beta2.4\TVAL3_beta2.4\Utilities\MRImask.m, 477 , 2007-11-08
ADMM-MATLAB\ADMM-MATLAB\TVAL3_beta2.4\TVAL3_beta2.4\Utilities\ScaleA.m, 629 , 2009-05-20
ADMM-MATLAB\ADMM-MATLAB\TVAL3_beta2.4\TVAL3_beta2.4\Utilities\Scaleb.m, 629 , 2009-05-20
ADMM-MATLAB\ADMM-MATLAB\TVAL3_beta2.4\TVAL3_beta2.4\warm_up.m, 503 , 2010-11-10
ADMM-MATLAB\ADMM-MATLAB\TVAL3_beta2.4.zip, 289508 , 2019-03-22
ADMM-MATLAB\ADMM-MATLAB\TVAL3_v1.0\demo.m, 1454 , 2019-04-17
ADMM-MATLAB\ADMM-MATLAB\TVAL3_v1.0\Demos\demo_barbara.m, 3196 , 2010-11-10
ADMM-MATLAB\ADMM-MATLAB\TVAL3_v1.0\Demos\demo_complex.m, 2530 , 2010-11-10
ADMM-MATLAB\ADMM-MATLAB\TVAL3_v1.0\Demos\demo_DFT.m, 3961 , 2010-11-10
ADMM-MATLAB\ADMM-MATLAB\TVAL3_v1.0\Demos\demo_phantom.m, 2611 , 2010-11-10
ADMM-MATLAB\ADMM-MATLAB\TVAL3_v1.0\Fast_Walsh_Hadamard_Transform\fWHtrans.cpp, 3225 , 2010-11-24
ADMM-MATLAB\ADMM-MATLAB\TVAL3_v1.0\Fast_Walsh_Hadamard_Transform\fWHtrans.mexa64, 8302 , 2010-11-29
ADMM-MATLAB\ADMM-MATLAB\TVAL3_v1.0\Fast_Walsh_Hadamard_Transform\fWHtrans.mexmaci, 9220 , 2010-11-29
ADMM-MATLAB\ADMM-MATLAB\TVAL3_v1.0\Fast_Walsh_Hadamard_Transform\fWHtrans.mexmaci64, 9072 , 2010-11-29
ADMM-MATLAB\ADMM-MATLAB\TVAL3_v1.0\Fast_Walsh_Hadamard_Transform\fWHtrans.mexw32, 8704 , 2010-11-29
ADMM-MATLAB\ADMM-MATLAB\TVAL3_v1.0\Fast_Walsh_Hadamard_Transform\fWHtrans.mexw64, 9216 , 2010-11-29
ADMM-MATLAB\ADMM-MATLAB\TVAL3_v1.0\Fast_Walsh_Hadamard_Transform\ifWHtrans.m, 446 , 2010-02-15
ADMM-MATLAB\ADMM-MATLAB\TVAL3_v1.0\Fast_Walsh_Hadamard_Transform\newFWHTcmp.fig, 11358 , 2010-02-17
ADMM-MATLAB\ADMM-MATLAB\TVAL3_v1.0\Fast_Walsh_Hadamard_Transform\readme.txt, 2115 , 2010-06-17
ADMM-MATLAB\ADMM-MATLAB\TVAL3_v1.0\Solver\ftvcs_alp.m, 15273 , 2010-11-10
ADMM-MATLAB\ADMM-MATLAB\TVAL3_v1.0\Solver\ftvcs_alp_old.m, 14446 , 2010-11-10
ADMM-MATLAB\ADMM-MATLAB\TVAL3_v1.0\Solver\ftvcs_al_opts.m, 5646 , 2010-11-10
ADMM-MATLAB\ADMM-MATLAB\TVAL3_v1.0\Solver\ftvcs_al_TVL2p.m, 14704 , 2010-11-10
ADMM-MATLAB\ADMM-MATLAB\TVAL3_v1.0\Solver\ftvcs_al_TVL2p_old.m, 13827 , 2010-11-10
ADMM-MATLAB\ADMM-MATLAB\TVAL3_v1.0\Solver\readme.txt, 2834 , 2010-06-17
ADMM-MATLAB\ADMM-MATLAB\TVAL3_v1.0\Solver\TVAL3.m, 674 , 2010-11-09
ADMM-MATLAB\ADMM-MATLAB\TVAL3_v1.0\User_Guide.pdf, 140166 , 2010-11-29
ADMM-MATLAB\ADMM-MATLAB\TVAL3_v1.0\Utilities\At_fWH.m, 284 , 2010-06-17
ADMM-MATLAB\ADMM-MATLAB\TVAL3_v1.0\Utilities\A_fWH.m, 244 , 2010-06-17
ADMM-MATLAB\ADMM-MATLAB\TVAL3_v1.0\Utilities\barbara256.tif, 107022 , 2009-06-15
ADMM-MATLAB\ADMM-MATLAB\TVAL3_v1.0\Utilities\defDDt.m, 379 , 2009-02-19
ADMM-MATLAB\ADMM-MATLAB\TVAL3_v1.0\Utilities\Fp1d.m, 197 , 2008-08-27
ADMM-MATLAB\ADMM-MATLAB\TVAL3_v1.0\Utilities\Fp2d.m, 326 , 2008-11-17
ADMM-MATLAB\ADMM-MATLAB\TVAL3_v1.0\Utilities\FpT1d.m, 233 , 2008-08-27
ADMM-MATLAB\ADMM-MATLAB\TVAL3_v1.0\Utilities\FpT2d.m, 265 , 2008-11-17
ADMM-MATLAB\ADMM-MATLAB\TVAL3_v1.0\Utilities\f_handleA.m, 202 , 2009-02-17
ADMM-MATLAB\ADMM-MATLAB\TVAL3_v1.0\Utilities\getA.m, 590 , 2009-02-09
ADMM-MATLAB\ADMM-MATLAB\TVAL3_v1.0\Utilities\isinInterval.m, 369 , 2008-06-14
ADMM-MATLAB\ADMM-MATLAB\TVAL3_v1.0\Utilities\MRImask.m, 477 , 2007-11-08
ADMM-MATLAB\ADMM-MATLAB\TVAL3_v1.0\Utilities\ScaleA.m, 629 , 2009-05-20
ADMM-MATLAB\ADMM-MATLAB\TVAL3_v1.0\Utilities\Scaleb.m, 629 , 2009-05-20
ADMM-MATLAB\ADMM-MATLAB\TVAL3_v1.0\warm_up.m, 507 , 2010-11-29
ADMM-MATLAB\ADMM-MATLAB\TVAL3_v1.0.zip, 291417 , 2019-03-22
ADMM-MATLAB\ADMM-MATLAB\User_Guide_beta2.4.pdf, 140176 , 2019-03-22
ADMM-MATLAB\ADMM-MATLAB\User_Guide_v1.0b.pdf, 149030 , 2019-03-22
ADMM-MATLAB\ADMM-MATLAB\TVAL3_beta2.4\TVAL3_beta2.4\Demos, 0 , 2010-11-10
ADMM-MATLAB\ADMM-MATLAB\TVAL3_beta2.4\TVAL3_beta2.4\Fast_Walsh_Hadamard_Transform, 0 , 2010-11-10
ADMM-MATLAB\ADMM-MATLAB\TVAL3_beta2.4\TVAL3_beta2.4\Solver, 0 , 2010-11-10
ADMM-MATLAB\ADMM-MATLAB\TVAL3_beta2.4\TVAL3_beta2.4\Utilities, 0 , 2010-06-17
ADMM-MATLAB\ADMM-MATLAB\TVAL3_beta2.4\TVAL3_beta2.4, 0 , 2010-11-10
ADMM-MATLAB\ADMM-MATLAB\TVAL3_v1.0\Demos, 0 , 2010-11-24
ADMM-MATLAB\ADMM-MATLAB\TVAL3_v1.0\Fast_Walsh_Hadamard_Transform, 0 , 2010-11-29
ADMM-MATLAB\ADMM-MATLAB\TVAL3_v1.0\Solver, 0 , 2019-03-24
ADMM-MATLAB\ADMM-MATLAB\TVAL3_v1.0\Utilities, 0 , 2010-06-17
ADMM-MATLAB\ADMM-MATLAB\TVAL3_beta2.4, 0 , 2019-03-22
ADMM-MATLAB\ADMM-MATLAB\TVAL3_v1.0, 0 , 2010-11-29
ADMM-MATLAB\ADMM-MATLAB, 0 , 2019-03-22
ADMM-MATLAB, 0 , 2019-04-16

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    （1）计算图像中每个像素点的LBP模式(等价模式,或者旋转不变+等价模式)。 （2）然后计算每个cell的LBP特征值直方图，然后对该直方图进行归一化处理(每个cell中，对于每个bin,h[i]/=sum,sum就是一副图像中所有等价类的个数)。 （3）最后将得到的每个cell的统计直方图进行连接成为一个特征向量，也就是整幅图的LBP纹理特征向量； 然后便可利用SVM或者其他机器学习算法进行分类识别了。((1) calculate the LBP pattern of each pixel in the image (equivalent mode, or rotation invariant + equivalent mode). (2) then the LBP eigenvalue histogram of each cell is calculated, and then the histogram is normalized (for each cell, for each bin, h[i]/=sum, sum is the number of all the equivalent classes in a pair of images). (3) finally, the statistical histogram of each cell is connected into a feature vector, that is, the LBP texture feature vector of the whole picture. Then, SVM or other machine learning algorithms can be used for classification and recognition.)
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