How can I undistort an image in Matlab using the known camera parameters?

twerdster picture twerdster · Aug 25, 2012 · Viewed 16.5k times · Source

This is easy to do in OpenCV however I would like a native Matlab implementation that is fairly efficient and can be easily changed. The method should be able to take the camera parameters as specified in the above link.

Answer

twerdster picture twerdster · Aug 25, 2012

The simplest and most common way of doing undistort (also called unwarp or compensating for lens distortion) is to do a forward distortion on a chosen output photo size and then a reverse mapping using bilinear interpolation.

Here is code I wrote for performing this:

function I = undistort(Idistorted, params)
fx = params.fx;
fy = params.fy;
cx = params.cx;
cy = params.cy;
k1 = params.k1;
k2 = params.k2;
k3 = params.k3;
p1 = params.p1;
p2 = params.p2;

K = [fx 0 cx; 0 fy cy; 0 0 1];

I = zeros(size(Idistorted));
[i j] = find(~isnan(I));

% Xp = the xyz vals of points on the z plane
Xp = inv(K)*[j i ones(length(i),1)]';

% Now we calculate how those points distort i.e forward map them through the distortion
r2 = Xp(1,:).^2+Xp(2,:).^2;
x = Xp(1,:);
y = Xp(2,:);

x = x.*(1+k1*r2 + k2*r2.^2) + 2*p1.*x.*y + p2*(r2 + 2*x.^2);
y = y.*(1+k1*r2 + k2*r2.^2) + 2*p2.*x.*y + p1*(r2 + 2*y.^2);

% u and v are now the distorted cooridnates
u = reshape(fx*x + cx,size(I));
v = reshape(fy*y + cy,size(I));

% Now we perform a backward mapping in order to undistort the warped image coordinates
I = interp2(Idistorted, u, v);

To use it one needs to know the camera parameters of the camera being used. I am currently using the PMD CamboardNano which according to the Cayim.com forums has the parameters used here:

params = struct('fx',104.119, 'fy', 103.588, 'cx', 81.9494, 'cy', 59.4392, 'k1', -0.222609, 'k2', 0.063022, 'k3', 0, 'p1', 0.002865, 'p2', -0.001446);

I = undistort(Idistorted, params);

subplot(121); imagesc(Idistorted);
subplot(122); imagesc(I);

Here is an example of the output from the Camboard Nano. Note: I artificially added border lines to see what the effect was of the distortion close to the edges (its much more pronounced): enter image description here