lk光流法matlab代码
时间: 2023-09-22 12:11:22 浏览: 47
以下是基于MATLAB实现的LK光流法的代码示例:
```matlab
% 读取两张图像
im1 = imread('img1.jpg');
im2 = imread('img2.jpg');
% 将图像转换为灰度图
im1gray = rgb2gray(im1);
im2gray = rgb2gray(im2);
% 设定窗口大小和迭代次数
winSize = 15;
maxIter = 100;
% 计算LK光流
[u,v] = LKflow(im1gray,im2gray,winSize,maxIter);
% 可视化光流
[X,Y] = meshgrid(1:size(im1gray,2),1:size(im1gray,1));
imshow(im1);
hold on;
quiver(X,Y,u,v);
```
其中,LKflow函数实现了LK光流法的计算过程。以下是LKflow函数的代码示例:
```matlab
function [u,v] = LKflow(im1,im2,winSize,maxIter)
% 将图像转换为double类型
im1 = im2double(im1);
im2 = im2double(im2);
% 计算图像梯度
Ix = conv2(im1,[-1 1],'same');
Iy = conv2(im1,[-1;1],'same');
It = im2 - im1;
% 初始化光流
u = zeros(size(im1));
v = zeros(size(im1));
% 设定高斯权重矩阵
G = fspecial('gaussian',[winSize winSize],2);
% 迭代计算光流
for i = 1:maxIter
% 计算误差
error = It + Ix.*u + Iy.*v;
% 计算局部加权平均
uAvg = conv2(u,G,'same');
vAvg = conv2(v,G,'same');
IxAvg = conv2(Ix.^2,G,'same');
IyAvg = conv2(Iy.^2,G,'same');
IxyAvg = conv2(Ix.*Iy,G,'same');
% 计算H矩阵的逆矩阵
H = [IxAvg IxyAvg; IxyAvg IyAvg];
Hinv = inv(H);
% 更新光流
delta = Hinv * [sum(sum(Ix.*error)); sum(sum(Iy.*error))];
u = uAvg - delta(1);
v = vAvg - delta(2);
end
end
```
该函数首先计算图像的梯度,然后初始化光流为0,并迭代计算光流。在每次迭代中,先计算误差,然后计算局部加权平均和H矩阵的逆矩阵,最后更新光流。