some problem in combine smoothing of different parameter?
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I have 4 matrix x=latitude, y=longitude, t=time and M= result of 1024*966 dimension want to smooth result across latitude using polynomial fit, then again want to smooth across time using cosine fit, can you please tell me how can I do?
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Image Analyst
2013년 8월 29일
편집: Image Analyst
2013년 8월 29일
What is a cosine fit? You mean like a Fourier series?
If you want a global polynomial fit, you can take row by row and use polyfit() to smooth it. For each row (untested)
orderOfPolynomial = 4; % Whatever order you want.
M_smoothed = M; % Initialize
for rowNumber = 1 : rows
oneRow = M(rowNumber, :);
coeffs = polyfit(1:columns, oneRow, orderOfPolynomial);
smoothedData = polyval(coeffs, 1:columns);
M_smoothed(rowNumber, :) = smoothedData;
end
imshow(M_smoothed, []);
If you want a localized sliding window fit, you can use a Savitzky-Golay filter, which is done by the sgolay() function in the Signal Processing Toolbox. If you don't have that toolbox, then you'll have to write it yourself using polyfit() over short sequences inside the window at each position, or see this. I also have a demo for sgolay() if you (or anyone else) have the Signal Processing Toolbox and want a demo.
댓글 수: 6
RS
2013년 8월 29일
Image Analyst
2013년 8월 29일
Did you look at the help for polyfit like it directed you to? See the mu and S? When it says that error, you need to use mu and S.
Image Analyst
2013년 8월 29일
Please please please read the help. Notice that you DID NOT use S and mu when you called polyfit the second time, nor did you use S and mu when you called polyval. The help will tell you these things. That's how I learned, so I'm sure you can learn that way too.
RS
2013년 8월 29일
Image Analyst
2013년 8월 29일
편집: Image Analyst
2013년 8월 29일
Explain what you're doing with x1, y1, xx, and xxx. And again, you need to pass S and mu into polyval().
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