1 算法介绍
模型参考这里
2 部分代码
% 'test_DeSCI.m' tests 'decompress snapshot compressive imaging (DeSCI)' algorithm for video reconstruction in
% 'coded aperture compressive temporal imaging (CACTI)'
% Reference
% [1] M. Qiao, Z. Meng, J. Ma, X. Yuan, Deep learning for video compressive
% sensing, APL Photonics 5, 030801 (2020).
% [2] Y. Liu, X. Yuan, J. Suo, D.J. Brady, and Q. Dai, Rank Minimization
% for Snapshot Compressive Imaging, IEEE Trans. Pattern Anal. Mach.
% Intell. (TPAMI), DOI:10.1109/TPAMI.2018.2873587, 2018.
% Contact
% Xin Yuan, Bell Labs, xyuan@bell-labs.com
% Mu Qiao, New Jersey Institute of Technology, muqiao@njit.edu
% Update Mar 13, 2020.
%% [0] environment configuration
clear;
clc;
close all
addpath(genpath('./DeSCI_algorithm')); % algorithms
datasetdir = './dataset'; % dataset dictionary
para.dataname = 'meas_waterBalloon_cr_10'; % selected 2D measurement
para.cr = str2double(para.dataname(end-1:end)); % compression ratio of the selected measurement, i.e., number of video frames to be recovered from each single 2D measurement
para.numRec = 1; % number of measurement frames to be reconstructed
datapath = sprintf('%s/%s.mat',datasetdir,para.dataname); % path of the selected 2D measurement
%% [1] load dataset
load(datapath); % load measurement
load('./dataset/mask.mat'); % load mask
meas = meas(:,:,1:para.numRec);
meas = 1850*meas./max(meas(:));
mask = double(mask(:,:,1:para.cr));
[nrow,ncol,~] = size(meas);
%% [2] ADMM-WNNM-TV
para.nframe = para.numRec;
para.MAXB = 255;
MAXB = para.MAXB;
para.Mfunc = @(z) A_xy(z,mask);
para.Mtfunc = @(z) At_xy_nonorm(z,mask);
para.Phisum = sum(mask.^2,3);
para.Phisum(para.Phisum==0) = 1;
para.flag_iqa = false; % disable image quality assessments in iterations
para.acc = 1; % enable acceleration
para.flag_iqa = false; % disable image quality assessments in iterations
para.projmeth = 'admm_res'; % projection method
% (GAP for noiseless or ADMM for noisy)
para.gamma = 1; % regularization factor for noise suppression
para.denoiser = 'wnnm'; % WNNM denoising
para.wnnm_int_fwise = true; % enable GAP-WNNM integrated (with frame-wise denoising)
para.blockmatch_period = 20; % period of block matching
para.sigma = [50 45 40]/MAXB; % noise deviation (to be estimated and adapted)
para.vrange = 1; % range of the signal
para.maxiter = [50 50 50]; % first trial
para.patchsize = 24; % patch size
para.iternum = 1; % iteration number in WNNM
para.enparfor = true; % enable parfor
para.numworkers = 12;
if para.enparfor % if parfor is enabled, start parpool in advance
mycluster = parcluster('local');
delete(gcp('nocreate')); % delete current parpool
ord = 0;
while para.cr/2^ord > mycluster.NumWorkers
ord = ord+1;
end
poolobj = parpool(mycluster,min(max(floor(para.cr/2^ord),1),para.numworkers));
end
[vadmmwnnmtv,~,~,tadmmwnnm] = ...
admmdenoise_cacti(mask,meas,[],[],para);
%% [3] show results in figure
% [3.0] rotate and crop
recon = vadmmwnnmtv;
recon_rotate = zeros(725,725,para.numRec*para.cr);
for np=1:para.numRec*para.cr
recon_rotate(:,:,np) = imrotate(recon(:,:,np),-135);
end
recon_rotate = recon_rotate(182:182+363,182:182+363,:);
recon_rotate = recon_rotate/max(recon_rotate(:));
% [3.1] show results in figure
figure;
for i=1:para.numRec*para.cr
imshow(recon_rotate(:,:,i));
pause(0.2);
end
3 仿真结果
4 参考文献
[1]王云常,戴朱祥,李涛.基于A星算法与人工势场法的无人机路径规划[J].扬州大学学报(自然科学版),2019,22(03):36-38+49.
博主简介：擅长智能优化算法、神经网络预测、信号处理、元胞自动机、图像处理、路径规划、无人机等多种领域的Matlab仿真，相关matlab代码问题可私信交流。
部分理论引用网络文献，若有侵权联系博主删除。
