用数字散斑法在matlab中三维重建peaks函数
时间: 2024-05-13 11:17:19 浏览: 223
数字散斑法(Digital Holography)是一种非接触式三维检测技术,可以实现对物体的三维形态进行重建。下面是在MATLAB中利用数字散斑法对peaks函数进行三维重建的步骤:
1. 生成模拟全息图
```matlab
x = -10:0.1:10; % 定义x轴坐标范围
y = -10:0.1:10; % 定义y轴坐标范围
[X,Y] = meshgrid(x,y); % 生成网格坐标矩阵
Z = peaks(X,Y); % 计算peaks函数值
figure; surf(X,Y,Z); % 绘制三维图像
title('原始物体'); xlabel('x'); ylabel('y'); zlabel('z'); % 设置图像标题及坐标轴标签
axis tight; view(45,30); % 设置视角及坐标轴范围
```
2. 计算全息图
```matlab
lambda = 632.8e-9; % 激光波长
k = 2*pi/lambda; % 波数
z = 0.5; % 物体到CCD的距离
H = exp(1j*k*z)*exp(1j*k*(X.^2+Y.^2)/(2*z)).*fftshift(fft2(Z)); % 计算全息图
figure; imagesc(abs(H)); colormap(gray); % 绘制全息图像
title('全息图'); xlabel('x'); ylabel('y'); % 设置标题及坐标轴标签
axis equal; axis off; % 设置坐标轴范围及关闭坐标轴显示
```
3. 进行数字重建
```matlab
dx = 0.1; % CCD像素大小
M = size(H,1); % CCD像素数
L = lambda*z/dx; % 采样宽度
x = -L/2:dx:L/2-dx; % 采样点坐标范围
[X,Y] = meshgrid(x,x); % 生成采样网格坐标矩阵
R = sqrt(X.^2+Y.^2); % 采样点到中心的距离
kx = linspace(-pi/dx,pi/dx,M); % k_x坐标范围
[Kx,Ky] = meshgrid(kx,kx); % 生成k空间网格坐标矩阵
H_recon = zeros(size(H)); % 初始化重建后的全息图
for ii = 1:M
for jj = 1:M
if R(ii,jj) < L/2 % 采样点在圆形范围内
H_recon = H_recon + exp(-1j*k*(X(ii,jj)*Kx+Y(ii,jj)*Ky)/z).*H(ii,jj)*dx^2; % 重建公式
end
end
end
Z_recon = abs(ifft2(ifftshift(H_recon))); % 计算重建后的物体
figure; surf(X,Y,Z_recon); % 绘制三维图像
title('重建后的物体'); xlabel('x'); ylabel('y'); zlabel('z'); % 设置图像标题及坐标轴标签
axis tight; view(45,30); % 设置视角及坐标轴范围
```
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