How to smooth out or fit a surface?
47 visualizaciones (últimos 30 días)
Mostrar comentarios más antiguos
Jasnoor Singh
el 19 de Mayo de 2016
Comentada: Image Analyst
el 26 de Ag. de 2019
I have my data stored in a 44 by 44 matrix. When I plot this data, it has a lot of irregular peaks. I want a smooth surface instead. (I cannot use the cftool since I've got a long loop and cannot do it manually everytime.) Following is the code I'm using but I get an error saying that x and y should be a column matrix. If I remove the fit command line, the whole code runs perfectly fine. Can someone please point out my mistake or suggest changes to this code?
x = 1:44;
y = 1:44;
for i = 1:35
a = xlsread('\\uoa.auckland.ac.nz\engdfs\Homeair.xlsx',strcat('CO',int2str(46*i-18),':','EF',int2str(46*i+25)));
b = fit([x,y,],a,'lowess');
figure;
surf(x,y,b);
axis([0 44 0 44 -50 120]);
fname = sprintf('A%d.png',i);
saveas(gcf,fname);
end
0 comentarios
Respuesta aceptada
Chad Greene
el 20 de Mayo de 2016
If you have the image processing toolbox you could do a moving average or a moving median filter. Median filters tend to be good at removing lone bad grid points:
b_smooth = medfilt2(b,[5 5]));
performs a 5x5 moving median filter. Similarly you could do a 5x5 moving average:
b_smooth = imfilter(b,fspecial('average',[5 5]));
3 comentarios
Ke Chao
el 22 de Ag. de 2019
Hi, I have a question about this method. Since the window is [5 5], how about first/last 2 cols or rows? Do we need to extrapolate first and then doing moving average here?
Image Analyst
el 26 de Ag. de 2019
From the help for imfilter: "Input array values outside the bounds of the array are assigned the value X. When no padding option is specified, the default is 0." So you can see that when the window goes outside the image, and the center of the window is on the edge of the image or close to it, it assumes that the image is bigger and the value is zero out there. in other words, it does not shrink/crop the window as the window gets closer to the edge of the image.
Más respuestas (1)
Image Analyst
el 20 de Mayo de 2016
You can do a regression to fit a 2D polynomial surface to it. See John D'Errico's polyfitn: http://www.mathworks.com/matlabcentral/fileexchange/34765-polyfitn My demo of it is attached where I get a smooth background.
Ver también
Categorías
Más información sobre Surface and Mesh Plots en Help Center y File Exchange.
Productos
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!