why do I get a strange result with griddata cubic?

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Hi! I used the griddata cubic interpolation for the values of an image. I get this image that has a much higher range, from -300 to 400 aproximately. The non processed image has a range from 90 to 130. Any ideas why this happens?Thanks!
  3 Comments
Valeria Leto
Valeria Leto on 27 Jul 2021
u=[-20:0.05 :20];%5 cm
v=[0:-0.05:-20];
[Xq,Yq] = meshgrid(u,v);
Zq=zeros(length(v),length(u));
figure(30)
mesh(Xq,Yq,Zq)
view(2)
% Interpolazione con griddata: CUBIC
vq_4 = griddata(x,y,C,xq,yq,'cubic');
Unrecognized function or variable 'x'.
V_4=zeros(length(v),length(u));
for i=1:1:length(v)
V_4(i,:)=vq_4(1+(i-1)*801:1+(i-1)*801+800,1)';
end
%% PLOT
figure(34)
surf(Xq,Yq,Zq,V_4,'EdgeColor','none')
title('INTERPOLAZIONE CUBIC RISOLUZIONE 5 cm')
colormap gray
colorbar
axis equal
xlabel('est')
ylabel('nord')
% view(2)
Matt J
Matt J on 27 Jul 2021
The code you've posted does not run, I'm afraid:
Unrecognized function or variable 'x'.
Error in test (line 12)
vq_4 = griddata(x,y,C,xq,yq,'cubic');

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Accepted Answer

Walter Roberson
Walter Roberson on 27 Jul 2021
This is expected behavior when there are sharp edges, especially with a surrounding flat area.
B--
|
-A-
Especially if the region near B is dense, but the edge itself is sparse, then the polynomial generated near the edge needs to mathematically dip down below the base in order to gain the necessary steepness to match the flat control points to the left together with the high points to the right. Polynomials cannot just suddenly rise steeply without a leading edge, so the math needs to insert a downward edge to be able to rise from.
  9 Comments
Bruno Luong
Bruno Luong on 30 Jul 2021
working with xs/ys instead of x/y
xs = sx*x
ys = sy*y
sx, sy are appropriate scaling factors that you have to figure it out.

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