genfig11.m

来自「一种基于压缩感知技术的图像重建程序」· M 代码 · 共 56 行

% Figure 11: CSDN reconstruction of signal `Blocks', m = 2048, n = 512.

M = 2^11;
N = 2^9;

sig0 = MakeBlocks(M)';
qmf = MakeONFilter('Haar',1);

SNR = 5;
randn('seed', 2.055615866000000e+09);
[sig0 y]= NoiseMaker(sig0, SNR);

L = 3;
alpha0 = FWT_PO(y, L, qmf);

% Generate Random Dictionary
Phi = MatrixEnsemble(N,M);

% generate the vector S
S = Phi * alpha0;

% Solve the BP problem
alpha = SolveBP(Phi, S, M, 20);
sig = IWT_PO(alpha,L,qmf);

% Solve the BPDN problem
alpha2 = SolveBP(Phi, S, M, 20, 4*sqrt(2*log(M)));
sig2 = IWT_PO(alpha2,L,qmf);

subplot(3,2,1); plot(y); 
axis([0 M -10 20]); title('(a) Noisy Signal');
subplot(3,2,2); PlotWaveCoeff(alpha0, L, 0);  
title('(b) Noisy wavelet coefficients');

subplot(3,2,3); plot(sig); 
axis([0 M -10 20]); title('(c) CS Reconstruction, n = 512');
subplot(3,2,4); PlotWaveCoeff(alpha, L, 0);  
title('(d) CS Reconstruction');

subplot(3,2,5); plot(sig2); 
axis([0 M -10 20]); title('(e) CSDN Reconstruction, n = 512');
subplot(3,2,6); PlotWaveCoeff(alpha2, L, 0);  
title('(f) CSDN Reconstruction');

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% Copyright (c) 2006. Yaakov Tsaig
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% Part of SparseLab Version:100
% Created Tuesday March 28, 2006
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