代码搜索：图像加密
找到约 10,000 项符合「图像加密」的源代码
代码结果 10,000
www.eeworm.com/read/365858/9843296
m ksw_2d_qiongju.m
%%%利用二维最佳直方图熵法（KSW熵法）及穷举法实现灰度图像阈值分割
%%%主程序
%%初始部分，读取图像及计算相关信息
clear;
close all;
clc;
%format long;
I=imread('rice_noise.tif');
windowsize=3;
I_temp=I;
for i=2:255
fo
www.eeworm.com/read/365858/9843305
asv 2d_ksw_qiongju.asv
%%%利用二维最佳直方图熵法（KSW熵法）及穷举法实现灰度图像阈值分割
%%%主程序
%%初始部分，读取图像及计算相关信息
clear;
close all;
clc;
format long;
I=imread('rice.tif');
windowsize=3;
I_temp=I;
for i=2:255
for j=2:2
www.eeworm.com/read/365858/9843329
m ksw_2d_ga.m
%%%利用二维最佳直方图熵法（KSW熵法）及传统遗传算法实现灰度图像阈值分割
%%%主程序
%%初始部分，读取图像及计算相关信息
clear;
close all;
clc;
%format long;
I=imread('Lenna.bmp');
windowsize=3;
I_temp=I;
for i=2:255
for j=
www.eeworm.com/read/365858/9843366
asv ksw_ga_improve.asv
%%%利用最佳直方图熵法（KSW熵法）及改进遗传算法实现灰度图像阈值分割
%%%主程序
%%初始部分，读取图像及计算相关信息
clear;
close all;
clc;
I=imread('rice_noise.tif');
hist=imhist(I);
total=0;
for i=0:255
total=total+hist(i+1)
www.eeworm.com/read/365858/9843375
asv ksw_ga.asv
%%%利用最佳直方图熵法（KSW熵法）及传统遗传算法实现灰度图像阈值分割
%%%主程序
%%初始部分，读取图像及计算相关信息
clear;
close all;
clc;
I=imread('rice.tif');
hist=imhist(I);
total=0;
for i=0:255
total=total+hist(i+1);
end
www.eeworm.com/read/365858/9843395
asv ksw_2d_ga.asv
%%%利用二维最佳直方图熵法（KSW熵法）及传统遗传算法实现灰度图像阈值分割
%%%主程序
%%初始部分，读取图像及计算相关信息
clear;
close all;
clc;
%format long;
I=imread('rice.tif');
windowsize=3;
I_temp=I;
for i=2:255
for j=2
www.eeworm.com/read/168154/9936491
m mybilinear.m
%双线性插值算法的实现
% mybilinear.m
A = imread('D:\MATLAB7.0\images\Fig7.01.jpg');
j = 1; %j:缩小尺度，其对应缩小倍数为:2^j
[A,nr,nc]=myDWT2(A,j); %小波缩小图像
A = A(1:nr,1:nc);
imshow(A,[]); %显示缩小图像
%%%%%%%%%%%%%%%
www.eeworm.com/read/163479/10157907
m softness.m
clc
clear
close all
a0=imread('D:\Mary.bmp');
subplot(221);
imshow(a0);
title('原图像');
a= imnoise(a0,'salt & pepper',0.02);
a0=double(a0);
b=zeros(1,256);
c=[b;a0;b];
%给图像矩阵数据的最左和最右加入两列0
d=
www.eeworm.com/read/163479/10157921
m sp.m
clc
clear
close all
a0=imread('D:\Mary.bmp');
subplot(221);
imshow(a0);
title('原图像');
a= imnoise(a0,'salt & pepper',0.02);
a0=double(a0);
b=zeros(1,256);
c=[b;a0;b];
%给图像矩阵数据的最左和最右加入两列0
d=
www.eeworm.com/read/357171/10214038
m 13-11.m
I = imread('saturn.tif');
J = imnoise(I,'salt & pepper',0.02);
%图像添加盐椒噪声
subplot(121),imshow(J)
title('含有噪声的原图像')
J=double(J);
f=fft2(J);
g=fftshift(f);
[M,N]=size(f);
n=3;d0=20;
n1=floor(M/