thanks for share. But I have a problem: "??? Maximum recursion limit of 500 reached. Use
set(0,'RecursionLimit',N)
to change the limit. Be aware that exceeding your available stack
space can
crash MATLAB and/or your computer.
Error in ==> imbmpinfo>decodeCompression"
I'm using Matlab 7.8.0(R2009a)
Can you help me !
There is an issue regarding the sampling with this approach. Since the code simply samples the closest value the result is heavily undersampled in some regions (r>>), while it is oversampled in others (r<<).
It would be interesting to have a correct approach that satisfies signal processing criteria (e.g. smooth oversampled regions and grey values where undersampled black and white values come together.
Sorry, That looks a little unclear. Here it is again
function imC = Polar2Im(imP,W,method)
%Polar2Im turns a polar image (imP) into a cartesian image (imC) of width W
%method can be: '*linear', '*cubic', '*spline', or '*nearest'.
imP(isnan(imP))=0;
w = round(W/2);
xy = (1:W-w);
[M N P]= size(imP);
[x y] = meshgrid(xy,xy);
n = round(N/4);
rr = linspace(1,w,M);
W1 = w:-1:1;
PM = [2 1 3;1 2 3;2 1 3;1 2 3];
W2 = w+1:2*w;
nn = [1:n; n+1:2*n; 2*n+1:3*n; 3*n+1:N;];
w1 = [W1;W2;W2;W1];
w2 = [W2;W2;W1;W1];
aa = linspace(0,90*pi/180,n);
r = sqrt(x.^2 + y.^2);
a = atan2(y,x);
imC= zeros(W,W,P);
for i=1:4 %turn each quarter into a cartesian image
imC(w1(i,:),w2(i,:),:)=permute(interp2(rr,aa,imP(:,nn(i,:))',r,a,method),PM(i,:));
end
imC(isnan(imC))=0;
Hi
Thank you, this code is great, but takes a little too long for my application. After reading the thread I wrote similar code which works ~12 times faster for the PolarToIm section. It doesn't have quite the same functionality but I thought I would share it here in case others are having the same problem
function imC = Polar2Im(imP,W,method)
%Polar2Im turns a polar image (imP) into a cartesian image (imC) of width W
%method can be: '*linear', '*cubic', '*spline', or '*nearest'.
imP(isnan(imP))=0;
w = round(W/2); [M N P]= size(imP);
xy = (1:W-w); [x y] = meshgrid(xy,xy);
n = round(N/4); rr = linspace(1,w,M);
W1 = w:-1:1; PM = [2 1 3;1 2 3;2 1 3;1 2 3];
W2 = w+1:2*w; nn = [1:n; n+1:2*n; 2*n+1:3*n; 3*n+1:N;];
w1 = [W1;W2;W2;W1]; aa = linspace(0,90*pi/180,n);
w2 = [W2;W2;W1;W1]; r = sqrt(x.^2 + y.^2);
a = atan2(y,x); imC= zeros(W,W,P);
for i=1:4 %turn each quarter into a cartesian image
imC(w1(i,:),w2(i,:),:) = permute(interp2(rr,aa,imP(:,nn(i,:))',r,a,method),PM(i,:));
end
imC(isnan(imC))=0;
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