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⛄ 内容介绍
针对数字图像在处理过程中容易产生模糊的现象,提出了基于无参考图像质量评价的自适应反卷积去模糊算法
⛄ 部分代码
clear all
close all
clc
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Demo file for deconvtv
% Image deblurring
%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Prepare images
f_orig = im2double(imread('./data/building.jpg'));
[rows cols colors] = size(f_orig);
H = fspecial('gaussian', [9 9], 2);
g = imfilter(f_orig, H, 'circular');
g = imnoise(g, 'gaussian', 0, 0.00001);
% Setup parameters (for example)
opts.rho_r = 2;
opts.beta = [1 1 0];
opts.print = true;
opts.alpha = 0.7;
opts.method = 'l2';
% Setup mu
mu = 10000;
% Main routine
tic
out = deconvtv(g, H, mu, opts);
toc
% Display results
figure(1);
subplot(121)
imshow(g);
title('input');
subplot(122)
imshow(out.f);
title('output');
⛄ 运行结果
⛄ 参考文献
[1] S.H. Chan, R. Khoshabeh, K.B. Gibson, P.E. Gill, and T.Q. Nguyen, “An augmented Lagrangian method for total variation image restoration,” IEEE Trans. Image Process., vol. 20, no. 11, pp.3097–3111, Nov. 2011.