| Description |
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. |
