|Image Processing Toolbox User's Guide|
The windowing method involves multiplying the ideal impulse response with a window function to generate a corresponding filter, which tapers the ideal impulse response. Like the frequency sampling method, the windowing method produces a filter whose frequency response approximates a desired frequency response. The windowing method, however, tends to produce better results than the frequency sampling method.
The toolbox provides two functions for window-based filter design,
fwind1 designs a two-dimensional filter by using a two-dimensional window that it creates from one or two one-dimensional windows that you specify.
fwind2 designs a two-dimensional filter by using a specified two-dimensional window directly.
fwind1 supports two different methods for making the two-dimensional windows it uses:
The example below uses
fwind1 to create an 11-by-11 filter from the desired frequency response
Hd. Here, the
hamming function from the Signal Processing Toolbox is used to create a one-dimensional window, which
fwind1 then extends to a two-dimensional window.
Hd = zeros(11,11); Hd(4:8,4:8) = 1; [f1,f2] = freqspace(11,'meshgrid'); mesh(f1,f2,Hd), axis([-1 1 -1 1 0 1.2]), colormap(jet(64)) h = fwind1(Hd,hamming(11)); figure, freqz2(h,[32 32]), axis([-1 1 -1 1 0 1.2])
Desired Two-Dimensional Frequency Response (left) and Actual Two-Dimensional Frequency Response (right)
|Frequency Sampling Method||Creating the Desired Frequency Response Matrix|
© 1994-2005 The MathWorks, Inc.