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Pnmconvol User Manual(0) Pnmconvol User Manual(0)
NAME
pnmconvol - general MxN convolution on a Netpbm image
SYNOPSIS
pnmconvol { -matrix=convolution_matrix | -matrixfile=filename[,file-
name[, ...]] } [-normalize] [-bias=n]
[netpbmfile]
pnmconvol convolution_matrix_file [-normalize] [-nooffset] [netpbmfile]
Minimum unique abbreviation of option is acceptable. You may use dou-
ble hyphens instead of single hyphen to denote options. You may use
white space in place of the equals sign to separate an option name from
its value.
DESCRIPTION
This program is part of Netpbm(1).
pnmconvol reads a Netpbm image as input, convolves it with a specified
convolution matrix, and writes a Netpbm image 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 (sometimes called a convolution kernel), which
you supply in one of several ways. See
Convolution Matrix <#convolutionmatrix> .
At the edges of the convolved image, where the convolution matrix would
extend over the edge of the image, pnmconvol just copies the input pix-
els directly to the output. It's often better to deal with the pixels
near an edge by assuming some blank or background color beyond the
edge. To do that, use pnmpad to add a margin all around whose size is
half that of your convolution matrix size, not counting its center, in
the same dimension. (E.g. if your convolution matrix is 5 wide by 3
high, use pnmpad -left=2 -right=2 -top=1 -bottom=1). Feed that en-
larged image to pnmconvol, then use pamcut to chop the edges off the
convolved output, getting back to your original image dimensions.
(E.g. pamcut -left=2 -right=-2 -top=1 -bottom=-1).
The convolution computation can result in a value which is outside the
range representable in the output. When that happens, pnmconvol just
clips the output, which means brightness is not conserved.
To avoid clipping, you may want to scale your input values. For exam-
ple, if your convolution matrix might produce an output value as much
as double the maximum value in the input, then make sure the maxval of
the input (which is also the maxval of the output) is at least twice
the actual maximum value in the input.
Clipping negative numbers deserves special consideration. If your con-
volution matrix includes negative numbers, it is possible for pnmconvol
to calculate an output pixel as a negative value, which pnmconvol would
of course clip to zero, since Netpbm formats cannot represent negative
numbers.
Convolution Matrix
There are three ways to specify the convolution matrix:
o directly with a -matrix option.
o In a file (or set of them) named by a -matrixfile option, whose
contents are similar to a -matrix option value.
o With a special PNM file.
The PNM file option is the hardest, and exists only because until
Netpbm 10.49 (December 2009), it was the only way.
The regular convolution matrix file is slightly easier to read than the
-matrix option value, and makes your command line less messy, but re-
quires you to manage a separate file. With the file, you can have sep-
arate convolution matrices for the individual color components, which
you can't do with -matrix.
In any case, the convolution matrix pnmconvol uses is a matrix of real
numbers. They can be whole or fractional, positive, negative, or zero.
The convolution matrix always has an odd width and height, so that
there is a center element. pnmconvol figuratively places that center
element over a pixel of the input image and weights that pixel and its
neighbors as indicated by the convolution matrix to produce the pixel
in the same location of the output image.
For a normal convolution, where you're neither adding nor subtracting
total value from the image, but merely moving it around, you'll want to
make sure that all the numbers in the matrix add up to 1. If they
don't, pnmconvol warns you.
The elements of the matrix are actually tuples, one for each sample in
the input. (I.e. if the input is an RGB image, each element of the
convolution matrix has one weight for red, one for green, and one for
blue.
Directly On the Command Line
Here are examples of a -matrix option:
-matrix=0,.2,0;.2,.2,.2;0,.2,0
-matrix=-1,3,-1
The value consists of each row of the matrix from top to bottom, sepa-
rated by semicolons. Each row consists of the elements of the row from
left to right, separated by commas. You must of course have the same
number of elements in each row. Each element is a decimal floating
point number and is the weight to give to each component of a pixel
that corresponds to that matrix location.
Note that when you supply this option via a shell, semicolon (";")
probably means something to the shell, so use quotation marks.
There is no way with this method to have different weights for differ-
ent components of a pixel.
The -normalize option is often quite handy with -matrix because it lets
you quickly throw together the command without working out the math to
make sure the matrix isn't biased. Note that if you use the -normalize
option, the weights in the matrix aren't actually the numbers you spec-
ify in the -matrix option.
Regular Matrix File
Specify the name of the matrix file with a -matrixfile option. Or
specify a list of them, one for each plane of the image.
Examples:
-matrixfile=mymatrix
-matrixfile=myred,mygreen,myblue
Each file applies to one plane of the image (e.g. red, green, or blue),
in order. The matrix in each file must have the same dimensions. If
the input image has more planes than the number of files you specify,
the first file applies to the extra planes as well.
pnmconvol interprets the file as text, with lines delimited by Unix
newline characters (line feeds).
Each line of the file is one row of the matrix, in order from top to
bottom.
For each row, the file contains a floating point decimal number for
each element in the row, from left to right, separated by spaces. This
is not just any old white space -- it is exactly one space. Two spaces
in a row mean you've specified a null string for an element (which is
invalid). If you want to line up your matrix visually, use leading and
trailing zeroes in the floating point numbers to do it.
There is no way to put comments in the file. There is no signature or
any other metadata in the file.
Note that if you use the -normalize option, the weights in the matrix
aren't actually what is in the file.
PNM File
Before Netpbm 10.49 (December 2009), this was the only way to specify a
convolution matrix. pnmconvol used this method in an attempt to ex-
ploit the generic matrix processing capabilities of Netpbm, but as the
Netpbm formats don't directly allow matrices with the kinds of numbers
you need in a convolution matrix, it is quite cumbersome. In fact,
there simply is no way to specify some convolution matrices with a le-
gal Netpbm image, so to make it work, pnmconvol has to relax the Netpbm
file requirement that sample values be no greater than the image's max-
val. I.e. it isn't even a real PNM file.
The way you select this method of supplying the convolution matrix is
to not specify -matrix or -matrixfile. When you do that, you must
specify a second non-option argument -- that is the name of the PNM
file (or PNM equivalent PAM file).
There are two ways pnmconvol interprets the PNM convolution matrix im-
age pixels as weights: with offsets, and without offsets.
The simpler of the two is without offsets. That is what happens when
you specify the -nooffset option. In that case, pnmconvol simply nor-
malizes the sample values in the PNM image by dividing by the maxval.
For example, here is a sample convolution file that causes an output
pixel to be a simple average of its corresponding input pixel and its 8
neighbors, resulting in a smoothed image:
P2
3 3
18
2 2 2
2 2 2
2 2 2
(Note that the above text is an actual PGM file -- you can cut and
paste it. If you're not familiar with the plain PGM format, see the
PGM format specification(5)).
pnmconvol divides each of the sample values (2) by the maxval (18) so
the weight of each of the 9 input pixels gets is 1/9, which is exactly
what you want to keep the overall brightness of the image the same.
pnmconvol creates an output pixel by multiplying the values of each of
9 pixels by 1/9 and adding.
Note that with maxval 18, the range of possible values is 0 to 18. Af-
ter scaling, the range is 0 to 1.
For a normal convolution, where you're neither adding nor subtracting
total value from the image, but merely moving it around, you'll want to
make sure that all the scaled values in (each plane of) your convolu-
tion PNM add up to 1, which means all the actual sample values add up
to the maxval. Alternatively, you can use the -normalize option to
scale the scaled values further to make them all add up to 1 automati-
cally.
When you don't specify -nooffset, pnmconvol applies an offset, the pur-
pose of which is to allow you to indicate negative weights even though
PNM sample values are never negative. In this case, pnmconvol sub-
tracts half the maxval from each sample and then normalizes by dividing
by half the maxval. So to get the same result as we did above with
-nooffset, the convolution matrix PNM image would have to look like
this:
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 normalization step divides by 18/2 = 9, which makes it 1/9 -
exactly what you want. The equivalent matrix for 5x5 smoothing would
have maxval 50 and be filled with 26.
Note that with maxval 18, the range of possible values is 0 to 18. Af-
ter offset, that's -9 to 9, and after normalizing, the range is -1 to
1.
The convolution file will usually be a PGM, so that the same convolu-
tion gets applied to each color component. However, if you want to use
a PPM and do a different convolution to different colors, you can cer-
tainly do that.
Other Forms of Convolution
pnmconvol does only arithmetic, linear combination convolution. There
are other forms of convolution that are especially useful in image pro-
cessing.
pgmmedian does median filtering, which is a form of convolution where
the output pixel value, rather than being a linear combination of the
pixels in the window, is the median of a certain subset of them.
pgmmorphconv does dilation and erosion, which is like the median filter
but the output value is the minimum or maximum of the values in the
window.
OPTIONS
-matrix=convolution_matrix
The value of the convolution matrix. See Convolution Matrix
<#matrixopt> .
You may not specify both this and -matrixfile.
This option was new in Netpbm 10.49 (December 2009). Before
that, use a PNM file for the convolution matrix.
-matrixfile=filename
This specifies that you are supplying the convolution matrix in
a file and names that file. See Convolution Matrix
<#matrixfile> .
You may not specify both this and -matrix.
This option was new in Netpbm 10.49 (December 2009). Before
that, use a PNM file for the convolution matrix.
-normalize
This option says to adjust the weights in your convolution ma-
trix so they all add up to one. You usually want them to add up
to one so that the convolved result tends to have the same over-
all brightness as the input. With -normalize, pnmconvol scales
all the weights by the same factor to make the sum one. It does
this for each plane.
This can be quite convenient because you can just throw numbers
into the matrix that have roughly the right relationship to each
other and let pnmconvol do the work of normalizing them. And
you can adjust a matrix by raising or lowering certain weights
without having to modify all the other weights to maintain nor-
malcy. And you can use friendly integers.
Example:
$ pnmconvol myimage.ppm -normalize -matrix=1,1,1;1,1,1;1,1,1
This is of course a basic 3x3 average, but without you having to
specify 1/9 (.1111111) for each weight.
This option was new in Netpbm 10.50 (March 2010). But before
Netpbm 10.79 (June 2017), it has no effect when you specify the
convolution matrix via pseudo-PNM file.
-bias=n
This specifies an amount to add to the convolved value for each
sample.
The purpose of this addition is normally to handle negative con-
volution results. Because the convolution matrix can contain
negative numbers, the convolved value for a pixel could be nega-
tive. But Netpbm formats cannot contain negative sample values,
so without any bias, such samples would get clipped to zero.
The bias allows the output image to retain the information, and
a program that pocesses that output, knowing the bias value,
could reconstruct the real convolved values.
For example, with bias=100, a sample whose convolved value is -5
appears as 95 in the output, whereas a sample whose convolved
value is 5 appears as 105 in the output.
A typical value for the bias is half the maxval, allowing the
same range on either side of zero.
If the sample value, after adding the bias, is still less than
zero, pnmconvol clips it to zero. If it exceeds the maxval of
the output image, it clips it to the maxval.
The default is zero.
This option was new in Netpbm 10.68 (September 2014).
-nooffset=
This is part of the obsolete PNM image method of specifying the
convolution matrix. See Convolution Matrix <#matrixpnm> .
HISTORY
The -nooffset option was new in Netpbm 10.23 (July 2004), making it
substantially easier to specify a convolution matrix, but still hard.
In Netpbm 10.49 (December 2009), the PNM convolution matrix tyranny was
finally ended with the -matrix and -matrixfile options. In between,
pnmconvol was broken for a while because the Netpbm library started en-
forcing the requirement that a sample value not exceed the maxval of
the image. pnmconvol used the Netpbm library to read the PNM convolu-
tion matrix file, but in the pseudo-PNM format that pnmconvol uses, a
sample value sometimes has to exceed the maxval.
SEE ALSO
pnmsmooth(1), pgmmorphconv(1), pgmmedian(1), pnmnlfilt(1), pgmker-
nel(1), pamgauss(1), pammasksharpen(1), pnmpad(1), pamcut(1), pnm(5)
AUTHORS
Copyright (C) 1989, 1991 by Jef Poskanzer. Modified 26 November 1994
by Mike Burns, burns@chem.psu.edu
DOCUMENT SOURCE
This manual page was generated by the Netpbm tool 'makeman' from HTML
source. The master documentation is at
http://netpbm.sourceforge.net/doc/pnmconvol.html
netpbm documentation 30 April 2017 Pnmconvol User Manual(0)
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