# phpman > man > pnmconvol(1)

> **TLDR:** Convolute a PNM image.
>
- Convolve a PNM image with the specified convolution matrix:
  `pnmconvol -matrix=-1,3,-1 {{path/to/image.pnm}} > {{path/to/output.pnm}}`
- Convolve a PNM image with the convolution matrix in the specified files, one for each layer in the input image:
  `pnmconvol -matrixfile {{path/to/matrix1,path/to/matrix2,...}} {{path/to/image.pnm}} > {{path/to/output.pnm}}`
- Convolve a PNM image with the convolution matrix in the specified PNM file:
  `pnmconvol {{path/to/matrix.pnm}} {{path/to/image.pnm}} > {{path/to/output.pnm}}`
- Normalize the weights in the convolution matrix such that they add up to one:
  `pnmconvol -matrix=-1,3,-1 -normalize {{path/to/image.pnm}} > {{path/to/output.pnm}}`

*Source: tldr-pages*

---

[pnmconvol(1)](https://www.chedong.com/phpMan.php/man/pnmconvol/1/markdown)                           General Commands Manual                          [pnmconvol(1)](https://www.chedong.com/phpMan.php/man/pnmconvol/1/markdown)



## 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 por‐
       table 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 num‐
       bers in the convolution file are offset by -maxval/2 to make signed numbers, and then normal‐
       ized, 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 offset 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)](https://www.chedong.com/phpMan.php/man/pnmsmooth/1/markdown), [**pnm**(5)](https://www.chedong.com/phpMan.php/man/pnm/5/markdown)


## AUTHORS
       Copyright (C) 1989, 1991 by Jef Poskanzer.
       Modified 26 November 1994 by Mike Burns, <burns@chem.psu.edu>



                                          26 November 1994                              [pnmconvol(1)](https://www.chedong.com/phpMan.php/man/pnmconvol/1/markdown)