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Full Discussion: "Smoothing" the data
Top Forums UNIX for Dummies Questions & Answers "Smoothing" the data Post 302600983 by cosmologist on Wednesday 22nd of February 2012 03:08:00 PM
Old 02-22-2012
Ok, I know what it is that confused me now Smilie

So in the example that you mentioned

Quote:
Originally Posted by Corona688
For these points:

Code:
1
5
2
6
3
7
4
8
5
9

for a boxcar average of width 3, would you want:

Code:
(1+5+2)/3, (5+2+6)/3, (2+6+3)/3, (6+3+7)/3, (3+7+4)/3, (7+4+8)/3, (4+5+5)/3, (8+5+9)/3

What I was thinking was:

Code:
(1+5+2)/3, (2+6+3)/3, (3+7+4)/3, (4+5+5)/3

[If I am using the mathematical terms correctly this is convolution with a rectangle function, a special case of the boxcar function]..

Is there a way to modify your code to get that? Smilie

Thanks again for all the help!
 

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pnmconvol(1)						      General Commands Manual						      pnmconvol(1)

NAME
pnmconvol - general MxN convolution on a portable anymap SYNOPSIS
pnmconvol convolutionfile [pnmfile] DESCRIPTION
Reads two portable anymaps as input. Convolves the second using the first, and writes a portable anymap as output. Convolution means replacing each pixel with a weighted average of the nearby pixels. The weights and the area to average are determined by the convolution matrix. The unsigned numbers in the convolution file are offset by -maxval/2 to make signed numbers, and then normalized, so the actual values in the convolution file are only relative. Here is a sample convolution file; it does a simple average of the nine immediate neighbors, resulting in a smoothed image: P2 3 3 18 10 10 10 10 10 10 10 10 10 To see how this works, do the above-mentioned offset: 10 - 18/2 gives 1. The possible range of values is from 0 to 18, and after the off- set that's -9 to 9. The normalization step makes the range -1 to 1, and the values get scaled correspondingly so they become 1/9 - exactly what you want. The equivalent matrix for 5x5 smoothing would have maxval 50 and be filled with 26. The convolution file will usually be a graymap, so that the same convolution gets applied to each color component. However, if you want to use a pixmap and do a different convolution to different colors, you can certainly do that. At the edges of the convolved image, where the convolution matrix would extend over the edge of the image, pnmconvol just copies the input pixels directly to the output. SEE ALSO
pnmsmooth(1), pnm(5) AUTHORS
Copyright (C) 1989, 1991 by Jef Poskanzer. Modified 26 November 1994 by Mike Burns, burns@chem.psu.edu 26 November 1994 pnmconvol(1)
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