清空筛选条件
清空筛选条件

how can I show the denoised image after applying pca to a noisy image.

6 次查看（过去 30 天）
Shaveta Arora
Shaveta Arora 2016-1-31
评论： Image Analyst 2021-8-5
im=imread('cameraman.tif'); im1=imresize(im,[50,50]); im=double(im1); figure(1);imshow(im,[]); sig=10; noi=sig*randn(size(im)); data=im+noi; figure(2);imshow(data,[]);
[m,n]=size(data);
mn = mean(data,2); data = data-repmat(mn,1,n); covari=data*data'/n-1; [PC,V] = eig(covari); diav = diag(V); [junk, rindices] = sort(-1*diav); V = diav(rindices); PC = PC(:,rindices);
  3 个评论
显示 1更早的评论
Shaveta Arora
Shaveta Arora 2016-1-31
im=imread('cameraman.tif');
im1=imresize(im,[50,50]);
im=double(im1);
figure(1);imshow(im,[]);
sig=10;
noi=sig*randn(size(im));
data=im+noi; %noised image
figure(2);
imshow(data,[]);
[m,n]=size(data);
mn = mean(data,2);
data = data-repmat(mn,1,n);
covari=data*data'/n-1;
[PC,V] = eig(covari);
diav = diag(V);
[junk, rindices] = sort(-1*diav);
V = diav(rindices);
PC = PC(:,rindices);
Shaveta Arora
Shaveta Arora 2016-1-31
PC represents principal components of noisy image i.e data. Now pls help me how to get the image from these PCs.

请先登录，再进行评论。

请先登录，再回答此问题。

回答（1 个）

Image Analyst
Image Analyst 2016-1-31
figure;
imshow(PC, [], 'InitialMagnification', 1600);
title('PC Image', 'FontSize', 20);

类别

在 Help Center 和 File Exchange 中查找有关 Dimensionality Reduction and Feature Extraction 的更多信息

标签

产品

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by