2-D Savitzky-Golay Smoothing Filter

i.e. the Polynomial smoothingfilter or the least-squares smoothing filter.
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Mise à jour 19 déc. 2003

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2-D Savitzky-Golay smoothing filter (i.e., the polynomial smoothing
filter, or the least-squares smoothing filter)

See Ref. [1] for details on the 1-D Savitzky-Golay smoothing filter.
One can also refer to the following URL where a program of
1-D Savitzky-Golay smoothing (and differentiation) filter is given:
http://www.mathworks.com/matlabcentral/fileexchange/loadFile.do?objectId=4038&objectType=file

See Ref. [2] and [3] for details on the 2-D Savitzky-Golay smoothing filter.

Usage:
h=sgsf_2d(x,y,px,py,flag_coupling)
x = x data point, e.g., -3:3
y = y data point, e.g., -2:2
px =x polynomial order default=1
py =y polynomial order default=1
flag_coupling = with or without the consideration of the coupling terms, between x and y. default=0

Example:
sgsf_2d(-3:3,-3:3,2,2)
sgsf_2d(-3:3,-3:3,2,2,1)

Author:
Jianwen Luo <luojw@bme.tsinghua.edu.cn, luojw@ieee.org> 2003-12-15
Department of Biomedical Engineering, Department of Electrical Engineering
Tsinghua University, Beijing 100084, P. R. China

Reference
[1]A. Savitzky and M. J. E. Golay, "Smoothing and Differentiation of Data by Simplified Least Squares Procedures," Analytical Chemistry, vol. 36, pp. 1627-1639, 1964.
[2]K. L. Ratzlaff and J. T. Johnson, "Computation of Two-Dimensional Polynomial Least-Squares Convolution Smoothing Integers," Analytical Chemistry, vol. 61, pp. 1303-1305, 1989.
[3]J. E. Kuo, H. Wang, and S. Pickup, "Multidimensional Least-Squares Smoothing Using Orthogonal Polynomials," Analytical Chemistry, vol. 63, pp. 630-635, 1991.

Citation pour cette source

Jianwen Luo (2024). 2-D Savitzky-Golay Smoothing Filter (https://www.mathworks.com/matlabcentral/fileexchange/4270-2-d-savitzky-golay-smoothing-filter), MATLAB Central File Exchange. Récupéré le .

Compatibilité avec les versions de MATLAB
Créé avec R13
Compatible avec toutes les versions
Plateformes compatibles
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Version Publié le Notes de version
1.0.0.0