matlab PIV代码
时间: 2023-10-04 11:11:11 浏览: 84
您好!以下是一个简单的Matlab PIV(Particle Image Velocimetry,粒子图像测速)代码示例:
```matlab
% 读取图像
image1 = imread('image1.jpg');
image2 = imread('image2.jpg');
% 转换为灰度图像
gray1 = rgb2gray(image1);
gray2 = rgb2gray(image2);
% 定义PIV参数
WindowSize = 32; % 窗口大小
Overlap = 0.5; % 窗口重叠比例
SearchArea = 64; % 搜索区域大小
SubpixelFactor = 4; % 亚像素插值因子
% 执行PIV算法
vectors = PIV(gray1, gray2, WindowSize, Overlap, SearchArea, SubpixelFactor);
% 可视化结果
imshow(image1);
hold on;
quiver(vectors(:,1), vectors(:,2), vectors(:,3), vectors(:,4), 'r');
hold off;
function vectors = PIV(image1, image2, WindowSize, Overlap, SearchArea, SubpixelFactor)
[height, width] = size(image1);
% 计算窗口间隔和重叠区域大小
StepSize = round(WindowSize * (1 - Overlap));
OverlapSize = round(WindowSize * Overlap / 2);
% 初始化矢量数组
numVectorsX = floor((width - WindowSize) / StepSize) + 1;
numVectorsY = floor((height - WindowSize) / StepSize) + 1;
vectors = zeros(numVectorsX * numVectorsY, 4);
% 遍历所有窗口
index = 1;
for y = 1:StepSize:height-WindowSize+1
for x = 1:StepSize:width-WindowSize+1
% 提取窗口图像
window1 = double(image1(y:y+WindowSize-1, x:x+WindowSize-1));
window2 = double(image2(y:y+WindowSize-1, x:x+WindowSize-1));
% 计算相关性
correlation = normxcorr2(window1, window2);
% 窗口的搜索区域
searchArea = correlation(OverlapSize+1:end-OverlapSize, OverlapSize+1:end-OverlapSize);
% 找到最大相关性位置
[~, maxIndex] = max(searchArea(:));
[subY, subX] = ind2sub(size(searchArea), maxIndex);
% 计算矢量位置(窗口左上角为原点)
vectorX = x + subX - 1;
vectorY = y + subY - 1;
% 计算亚像素位移
if SubpixelFactor > 1
subPixelSearchArea = correlation(subY+OverlapSize-SubpixelFactor:subY+OverlapSize+SubpixelFactor, ...
subX+OverlapSize-SubpixelFactor:subX+OverlapSize+SubpixelFactor);
[subPixelY, subPixelX] = find(subPixelSearchArea == max(subPixelSearchArea(:)), 1);
subPixelX = subPixelX - SubpixelFactor - 1;
subPixelY = subPixelY - SubpixelFactor - 1;
vectorX = vectorX + subPixelX / SubpixelFactor;
vectorY = vectorY + subPixelY / SubpixelFactor;
end
% 保存矢量
vectors(index, :) = [vectorX, vectorY, vectorX - x, vectorY - y];
index = index + 1;
end
end
% 去除无效矢量
vectors(any(isnan(vectors), 2), :) = [];
end
```
这个代码示例演示了如何使用Matlab进行基本的PIV图像处理。您可以将两幅图像作为输入,然后定义PIV算法的参数(窗口大小、重叠比例、搜索区域大小、亚像素插值因子),然后执行PIV算法并可视化结果。
请注意,这只是一个简单的示例代码,实际应用中可能需要根据具体情况进行更多的参数调整和图像预处理。希望对您有帮助!如果您有任何问题,请随时提问。