数字图像处理实验(9):PROJECT 04-05,Correlation in the Frequency Domain 标签: 图像处理MATLAB 2017-05-25 10:14
实验要求:
Objective:
To know how to implement correlation of 2 functions in the frequency domain and, using the fast algorithms.
Main requirements:
Ability of programming with C, C++, or Matlab.
Instruction manual:
Download Figs. 4.41(a) and (b) and duplicate Example 4.11 to obtain Fig. 4.41(e). Give the (x,y) coordinates of the location of the maximum value in the 2D correlation function. There is no need to plot the profile in Fig. 4.41(f).
实验只是要求给出二维相关函数中最大值位置的(x,y)坐标,没有必要绘制图中的轮廓。
程序实现步骤:
1、将两幅图像的大小都拓展298×298;
2、两幅图像的每个像素都乘以(-1)^(x+y),使其在频域位于中心位置;
3、做傅里叶变换,转换到频域;
4、在频域两幅图像,一个与另一个的共轭相乘计算相关函数;
5、作傅里叶逆变换转换回空间域;
6、乘以(-1)^(x+y),得到最终结果。
要求使用的两幅图:
Figs. 4.41(a):
Figs. 4.41(b):
实验代码:
% Correlation in the Frequency Domain close all; clc; clear all; % img_f1 = imread('Fig4.41(a).jpg'); img_f2 = imread('Fig4.41(b).jpg'); [M1, N1] = size(img_f1); [M2, N2] = size(img_f2); P = 298; Q = 298; img_fp1 = zeros(P, Q); img_fp2 = zeros(P, Q); img_fp1(1:M1, 1:N1) = img_f1(1:M1, 1:N1); img_fp2(1:M2, 1:N2) = img_f2(1:M2, 1:N2); for x = 1:P for y = 1:Q img_fp1(x, y) = img_fp1(x, y) .* (-1)^(x+y); img_fp2(x, y) = img_fp2(x, y) .* (-1)^(x+y); end end % 傅里叶变换 img_Fp1 = fft2(img_fp1); img_Fp2 = fft2(img_fp2); % 求共轭 img_Fp = img_Fp2 .* conj(img_Fp1); % 傅里叶变换 img_fp = ifft2(img_Fp); % 乘以(-1)^(x+y) for x = 1:P for y = 1:Q img_fp(x, y) = img_fp(x, y) .* (-1)^(x+y); end end img_fp = real(img_fp); img_fp = mat2gray(img_fp); % 显示结果 imshow(img_fp); max_value = max(max(img_fp)); [row col] = find(img_fp == max_value); disp(['max value is : ', num2str(max_value)]); disp(['row: ', num2str(row), ' col: ', num2str(col)]);
实验结果:
这是输出结果的图片,实验要求没必要显示出来。
最后求出的(x,y)位置的坐标。
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