Image Processing Using LSI Filters
Many useful image operations are implemented with linear shift-invariant
(LSI) filters. A smoothing operation is frequently a first step in
operations such as noise reduction, edge detection or interpolation. A
commonly used smoothing filter has constant coefficients. The effect of
smoothing or blurring an image is achieved by convolving the image with
such a filter. The third example will demonstrate the use of convolution
to "sharpen" an image by a method called unsharp masking. The
simplest form of unsharp masking may be implemented by subtracting a
scaled smoothed image from the original.
Here we smooth and sharpen image the "head" example image.
Here we display the three results.
Edge detection is an important step in many shape-based recognition tasks.
Edge detection is typically implemented as a convolution operation with
appropriately chosen differentiating filters. Two examples of edge
detection using two common edge filters, the Sobel gradient edge detector
and the Laplacian-of-Gaussian edge detector, conclude this section.
User's Guide: Sections 5.2, 5.3, 7.3.
Function Index: DiscreteConvolve, EdgeMagnitude, ImagePlus, LoGFilter, SobelFilter, Threshold, ZeroCrossing.