clear X = imread('wgxy.jpg'); I = rgb2gray(X); imshow(I); I=double(I); subplot(231); imshow(I,[]); title('原始图像'); axis square; disp('压缩前图像大小字节'); whos('I'); [c,s] = wavedec2(I,3,'bior3.7'); ca1 = appcoef2(c,s,'bior3.7',1); ch1 = detcoef2('h',c,s,1); cv1 = detcoef2('v',c,s,1); cd1 = detcoef2('d',c,s,1); a1 = wrcoef2('a',c,s,'bior3.7',1); h1 = wrcoef2('h',c,s,'bior3.7',1); v1 = wrcoef2('v',c,s,'bior3.7',1); d1 = wrcoef2('d',c,s,'bior3.7',1); c1=[a1,h1;v1,d1]; subplot(232); imshow(c1,[]); axis square; title('分解后低频和高频信息'); ca1 = appcoef2(c,s,'bior3.7',1); ca1 = wcodemat(ca1,500,'mat',0); a11 = wrcoef2('a',c,s,'bior3.7',1); subplot(233); imshow(a11,[]); axis square; title('第一次压缩图像'); disp('第一次压缩图像字节大小'); whos('ca1'); subplot(234); ca2 = appcoef2(c,s,'bior3.7',2); ca2 = wcodemat(ca2,500,'mat',0); a22 = wrcoef2('a',c,s,'bior3.7',2); imshow(a22,[]); axis square; title('第二次压缩图像'); disp('第二次压缩图像字节大小'); whos('ca2'); subplot(235); ca3 = appcoef2(c,s,'bior3.7',3); ca3 = wcodemat(ca3,500,'mat',0); a33 = wrcoef2('a',c,s,'bior3.7',3); imshow(a33,[]); axis square; title('第三次压缩图像'); disp('第三次压缩图像字节大小'); whos('ca3');想让第三次压缩的字节有变化怎么改程序

可以通过更改wcodemat函数中的压缩比例参数来改变第三次压缩后的字节大小。将500改成其他数值即可，例如改为250。具体地，将

ca3 = wcodemat(ca3,500,'mat',0);

改为

ca3 = wcodemat(ca3,250,'mat',0);

即可。

相关问题

Img = imread('wgxy.jpg'); imshow(Img); disp('原始图像字节::'); whos('Img') I = rgb2gray(Img); imshow(I); disp('灰度图像字节:'); whos('I'); J = dct2(I); figure, imshow(log(abs(J))), colorbar; b=uint32(15/100*1080); J=J(1:b,1:b); disp('分块后反变换前字节:'); whos('J'); J(1080,1080)=0 K = idct2(J); disp('离散余弦变换后字节:'); whos('K'); figure, imshow(I), title('原图'); figure, imshow(J), title('二维离散余弦变换结果'); figure, imshow(K, [0,255]), title('还原图');加一段程序把峰值信噪比显示出来，换一种方式

Img = imread('wgxy.jpg');
imshow(Img);
disp('原始图像字节::');
whos('Img')

I = rgb2gray(Img);
imshow(I);
disp('灰度图像字节:');
whos('I')

J = dct2(I);
figure, imshow(log(abs(J))), colorbar;
b=uint32(15/100*1080);
J=J(1:b,1:b);
disp('分块后反变换前字节:');
whos('J');
J(1080,1080)=0
K = idct2(J);
disp('离散余弦变换后字节:');
whos('K')

figure, imshow(I), title('原图');
figure, imshow(J), title('二维离散余弦变换结果');
figure, imshow(K, [0,255]), title('还原图');

MSE = sum(sum((double(I)-double(K)).^2))/(size(I,1)*size(I,2));
MAXI = max(I(:));
PSNR = 10*log10(MAXI^2/MSE);
disp(['峰值信噪比为: ', num2str(PSNR)]);

clear,clc % 导入图片和水印 I1=double(imread('img\Lena.bmp')); I2=double(imread('img\Baboon.bmp')); I3=double(imread("img\barbara.bmp")); I4=double(imread("img\elain.bmp")); inImg=double(im2bw(imread('img\w.bmp'))); %视觉密码加密水印 % 平移归一化、X-shearing归一化、Y-shearing归一化和缩放归一化 im=I1; [normim1, normtform1, xdata1, ydata1] = imnorm(im); im=I2; [normim2, normtform2, xdata2, ydata2] = imnorm(im); im=I3; [normim3, normtform3, xdata3, ydata3] = imnorm(im); im=I4; [normim4, normtform4, xdata4, ydata4] = imnorm(im);，其中normim1输出的图片形式是什么，怎么将其改成灰度图

在上述代码中，`normim1`是经过归一化处理后的图像，其形式是一个三维矩阵，包含红、绿、蓝三个通道的像素值。如果要将其转换为灰度图像，可以使用以下代码：

% 将 normim1 转换为灰度图像
gray_normim1 = rgb2gray(uint8(normim1));

% 显示灰度图像
imshow(gray_normim1);

首先将`normim1`转换为`uint8`类型的图像，然后使用`rgb2gray`函数将其转换为灰度图像，最后使用`imshow`函数显示灰度图像。