使用 Matlab 进行图像比较答案

【问题标题】：Image comparison using Matlab使用 Matlab 进行图像比较
【发布时间】：2017-12-14 23:23:38
【问题描述】：

我想在 Matlab 中比较两个图像（我了解到 Matlab 有更多用于比较图像和处理它们的功能）。任何人都可以提出一个好的和简单的方法来做同样的事情吗？并且图像需要完全相同。所以不需要考虑图像的亮度和位置。

我需要在两个月内完成我的项目，所以如果有人帮助我提供一个好的算法或方法，我会很高兴。

【问题讨论】：

标签： matlab

【解决方案1】：

当您将图像加载到 MATLAB 中时，它们会存储为矩阵。您可以用来比较矩阵的任何东西都可以比较图像（例如 ISEQUAL）。但是，如果您想在图像处理方面更多地比较图像，请查看图像处理工具箱的演示并查看 here 哪些演示（如果有）符合您对“比较”的定义。

【讨论】：

链接断开。请修复它。

【解决方案2】：

您可以使用 EMD 算法。它适用于直方图。下面是一些可能有帮助的代码：

function[d] = hcompare_EMD(h1,h2)
% This function calculates Earth Movers Distance between two normalized
% histograms h1 and h2. Normalized histogram is histogram h, that has at
% each i place in it, value:
% (number of picture pixels with gray level i-1) / 
% (total num of pixels in picture).


% ALternative fast way:
d = sum(abs(cumsum(h1) - cumsum(h2)));
end

两个图像的直方图是这样计算的：

function[h] = histImage(img)
% This function calculates normalized histogram of image.
% Normalized histogram is histogram h, that has at
% each i place in it, value:
% (number of picture pixels with gray level i-1) / 
% (total num of pixels in picture).
sum = 0;
[y,x] = size(img); % getting sizes of image  
h = zeros(1,256);    % creating output histogram array
for i = 1:1: y     % runing on rows
    for j = 1:1: x % running on colomns
        % gray level is addtess to cell in output histogram array
        % we add there 1 (bacause of current pixel (y,x) has this gray level
        h(img(i,j)) = h(img(i,j)) + 1;
        % pay attention to fact, that we use here pixel value as index!
    end
end

h = h./(y*x);
end

计算两幅图像直方图之间的距离（histArray, histPattern）：

function[dmap] = patDistMAp(histArray, histPattern)
% Given histograms of an image and pattern returns an array (image) 
% of distance values between
% img windows and pattern. Distance values are computed between the histograms
% of the windows and the pattern using the histogram distance function

[y,x,z] = size(histArray);
dmap = zeros(y,x);                  % output array

for i = 1:1: y       % runing on rows
    for j = 1:1: x   % running on colomns
        hist = histArray(i,j,:);
%         for k = 1:1:256             % making array 1x256 from 1x1x256
%             h1(k) = hist(1,1,k);    % there is a permute function,
%         end                         % but we will use it next time)
        h1 = permute(squeeze(hist),[2,1]);
        % Using temp variable, as MATLAB7 wants it:
        temp = hcompare_EMD(histPattern,h1);
        dmap(i,j) = temp;
    end
end

end

【讨论】：

【解决方案3】：

    a = imread('image1.jpg'); %reading images as array to variable 'a' & 'b'. 
    b = imread('image2.jpg'); 
    c = corr2(a,b);           %finding the correlation btwn two images 
    if c==1 
    disp('The images are same')%output display 
    else 
    disp('the images are not same') 
    end;

【讨论】：

【解决方案4】：

图片需要完全相同？

a = imread('image1.jpg');
b = imread('image2.jpg'); 
result = all(size(a) == size(b));
if result
    result = all(reshape(a,[],1)== reshape(b,[],1));
end

【讨论】：