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REALGraphics

Filter By Convolution

Issue: 7.3 (March/April 2009)
Author: JC Cruz
Author Bio: JC is a freelance technical writer living in British Columbia. He writes for various publications on Cocoa, Python and REALbasic, and spends time with his nephew. He can be reached at: anarakisware@gmail.com
Article Description: No description available.
Article Length (in bytes): 39,690
Starting Page Number: 31
Article Number: 7311
Resource File(s):

7311.zip Updated: 2009-03-02 13:37:09

Related Web Link(s):

http://www.apolloarchive.com/apollo_gallery.html
http://www.dfanning.com/ip_tips/sharpen.html
http://www.generation5.org/content/2004/noiseIntro.asp
http://en.wikipedia.org/wiki/Edge_detection
http://en.wikipedia.org/wiki/Matrix_
http://en.wikipedia.org/wiki/Noise_reduction
http://www.ph.tn.tudelft.nl/Courses/FIP/noframes/fip-Convolut-2.html

Excerpt of article text...

Welcome back to another installment of REALGraphics. Today's topic is the concept of convolution filters. First, we learn the concept of convolution and how it is used to filter image data. Then we learn the parts that make up a convolution filter. Next, we look at some examples of convolution filters. We then build and test a basic filter as a finite-state machine.

The Convolution Filter

The convolution filter is a feature found in many high-end image processing software programs. It belongs to a family of matrix algorithms. The filter works by first dividing the image data into small, equal-sized regions. To each region, it applies a set of constants by a process called convolution. The filter then uses the results to build a modified image.

Anatomy of a filter

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