Relay-Version: version B 2.10 5/3/83; site utzoo.UUCP Posting-Version: $Revision: 1.6.2.16 $; site datacube.UUCP Path: utzoo!watmath!clyde!burl!ulysses!ucbvax!decvax!cca!datacube!shep From: shep@datacube.UUCP Newsgroups: net.graphics Subject: Re: Re: FFT of image in sections ? Message-ID: <6700028@datacube.UUCP> Date: Wed, 14-Aug-85 09:22:00 EDT Article-I.D.: datacube.6700028 Posted: Wed Aug 14 09:22:00 1985 Date-Received: Fri, 23-Aug-85 23:55:19 EDT References: <208@mplvax.UUCP> Lines: 27 Nf-ID: #R:mplvax:-20800:datacube:6700028:000:1390 Nf-From: datacube!shep Aug 14 09:22:00 1985 In article <360@ur-laser.uucp> nitin@ur-laser.uucp (Nitin Sampat) writes: >We know that processing small images takes less time. Well, how does >one go about breaking up a large image and process it in sections, >and then most importantly, how does one put all these sections back >to get the FFT of the original image ? And carl lowenstein sdcsvax!mplvax!cdl writes: >Just a little philosophical fuel on the fire: The whole idea behind the >FFT (what makes it *F*ast) is that breaking a large dataset into sections, >processing the sections, and then recombining them is faster than processing >the whole thing all at once. (recursively, down to sections of size 2 or 4). Exactly! It is the representation of a one-dimensional string of numbers as a two-dimensional array that allows it to fall together. Two-dimensional image transforms are handled as the linear combination of two one-dimensional passes. (The DFT is separable.) Radix-2 and radix-4 butterflies are common only because of their ease of use on sequence lengths that are highly composite (i.e. powers of two). A radix-5 butterfly might be used for performing a 60 point FFT algorithm. Rabiner and Gold give a good discussion of this in their EE classic "Theory and Application of DSP". Shep Siegel UUCP: ihnp4!datacube!shep Datacube Inc.; 4 Dearborn Rd.; Peabody, Ma. 01960; 617-535-6644