Path: utzoo!yunexus!geac!syntron!jtsv16!uunet!seismo!sundc!pitstop!sun!amdcad!ames!ncar!tank!uxc!uxc.cso.uiuc.edu!urbsdc!kworrell
From: kworrell@urbsdc.Urbana.Gould.COM
Newsgroups: comp.graphics
Subject: Re: Image Processing question
Message-ID: <62300003@urbsdc>
Date: 19 Oct 88 14:29:00 GMT
Article-I.D.: urbsdc.62300003
References: <26451@ucbvax.BERKELEY.EDU>
Lines: 16
Nf-ID: #R:ucbvax.BERKELEY.EDU:26451:urbsdc:62300003:000:885
Nf-From: urbsdc.Urbana.Gould.COM!kworrell    Oct 19 09:29:00 1988


A standard way of doing this type of transformation is to take each pixel in the
output image, do the inverse scaling transform (to determine where on the original
image we should be looking to find relevant data) and do some kind of weighting
function of neighboring pixels to get a value.  There are several standard functions
(Nearest neighbor, bilinear, cubic ...) which trade image quality for speed.

Note that this doesn't just work for scaling.  Basically any xform will work.

Take a look at Rosenfeld & Kak or Ballard & Brown (or any other reasonable IP book)
for weights and algorithms.

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Kurt J. Worrell	                 USEnet1:    uunet!uiucuxc!urbsdc!kworrell
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