Linear Filtering
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Mathematica notebook. |
Many useful image processing operations may be implemented by filtering the image
with a selected filter.
Digital
Image Processing defines a large number of
smoothing, sharpening, noise reduction, and edge filters. Additional filters may be
easily added or designed using the filter design functionality of the package.
![[Graphics:Images/index_gr_1.gif]](Images/index_gr_1.gif)
BoxFilter, GaussianFilter, and SmoothingFilter
are all variants of so-called
smoothing filters. They produce a response that is a local (weighted) average of
the samples of a signal.
The Savitzky-Golay smoothing filter is an optimal filter that returns the best average
value, in the sense of least squares, for each neighborhood of image points. It is a good
general-purpose smoothing filter. Here we show the coefficients of a Savitzky-Golay
filter of order three and length five.
![[Graphics:Images/index_gr_2.gif]](Images/index_gr_2.gif)
![[Graphics:Images/index_gr_3.gif]](Images/index_gr_3.gif)
This loads an example image and computes a smoothed copy using the filter shown above.
![[Graphics:Images/index_gr_4.gif]](Images/index_gr_4.gif)
Here we display the two images.
![[Graphics:Images/index_gr_5.gif]](Images/index_gr_5.gif)
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