1Pnmconvol User Manual(0) Pnmconvol User Manual(0)
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6 pnmconvol - general MxN convolution on a Netpbm image
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10 pnmconvol { -matrix=convolution_matrix | -matrixfile=filename[,file‐
11 name[, ...]] } [-normalize] [-bias=n]
12 [netpbmfile]
14 pnmconvol convolution_matrix_file [-normalize] [-nooffset] [netpbmfile]
16 Minimum unique abbreviation of option is acceptable. You may use dou‐
18 ble hyphens instead of single hyphen to denote options. You may use
19 white space in place of the equals sign to separate an option name from
20 its value.
21
25 This program is part of Netpbm(1).
26 pnmconvol reads a Netpbm image as input, convolves it with a specified
28 convolution matrix, and writes a Netpbm image as output.
29 A command use for convolution is blurring. See examples in the pam‐
31 gauss(1) manual.
32 Convolution means replacing each pixel with a weighted average of the
35 nearby pixels. The weights and the area to average are determined by
36 the convolution matrix (sometimes called a convolution kernel), which
37 you supply in one of several ways. See
38 Convolution Matrix ⟨#convolutionmatrix⟩ .
39 At the edges of the convolved image, where the convolution matrix would
41 extend over the edge of the image, pnmconvol just copies the input pix‐
42 els directly to the output. It's often better to deal with the pixels
43 near an edge by assuming some blank or background color beyond the
44 edge. To do that, use pnmpad to add a margin all around whose size is
45 half that of your convolution matrix size, not counting its center, in
46 the same dimension. (E.g. if your convolution matrix is 5 wide by 3
47 high, use pnmpad -left=2 -right=2 -top=1 -bottom=1). Feed that
48 enlarged image to pnmconvol, then use pamcut to chop the edges off the
49 convolved output, getting back to your original image dimensions.
50 (E.g. pamcut -left=2 -right=-2 -top=1 -bottom=-1).
51 The convolution computation can result in a value which is outside the
53 range representable in the output. When that happens, pnmconvol just
54 clips the output, which means brightness is not conserved.
55 To avoid clipping, you may want to scale your input values. For exam‐
57 ple, if your convolution matrix might produce an output value as much
58 as double the maximum value in the input, then make sure the maxval of
59 the input (which is also the maxval of the output) is at least twice
60 the actual maximum value in the input.
61 Clipping negative numbers deserves special consideration. If your con‐
63 volution matrix includes negative numbers, it is possible for pnmconvol
64 to calculate an output pixel as a negative value, which pnmconvol would
65 of course clip to zero, since Netpbm formats cannot represent negative
66 numbers.
67 Convolution Matrix
71 There are three ways to specify the convolution matrix:
72 · directly with a -matrix option.
76 · In a file (or set of them) named by a -matrixfile option, whose
79 contents are similar to a -matrix option value.
80 · With a special PNM file.
83 The PNM file option is the hardest, and exists only because until
86 Netpbm 10.49 (December 2009), it was the only way.
87 The regular convolution matrix file is slightly easier to read than the
89 -matrix option value, and makes your command line less messy, but
90 requires you to manage a separate file. With the file, you can have
91 separate convolution matrices for the individual color components,
92 which you can't do with -matrix.
93 In any case, the convolution matrix pnmconvol uses is a matrix of real
95 numbers. They can be whole or fractional, positive, negative, or zero.
96 The convolution matrix always has an odd width and height, so that
98 there is a center element. pnmconvol figuratively places that center
99 element over a pixel of the input image and weights that pixel and its
100 neighbors as indicated by the convolution matrix to produce the pixel
101 in the same location of the output image.
102 For a normal convolution, where you're neither adding nor subtracting
104 total value from the image, but merely moving it around, you'll want to
105 make sure that all the numbers in the matrix add up to 1. If they
106 don't, pnmconvol warns you.
107 The elements of the matrix are actually tuples, one for each sample in
109 the input. (I.e. if the input is an RGB image, each element of the
110 convolution matrix has one weight for red, one for green, and one for
111 blue.
112 Directly On the Command Line
115 Here are examples of a -matrix option:
117 -matrix=0,.2,0;.2,.2,.2;0,.2,0
119 -matrix=-1,3,-1
121 The value consists of each row of the matrix from top to bottom, sepa‐
123 rated by semicolons. Each row consists of the elements of the row from
124 left to right, separated by commas. You must of course have the same
125 number of elements in each row. Each element is a decimal floating
126 point number and is the weight to give to each component of a pixel
127 that corresponds to that matrix location.
128 Note that when you supply this option via a shell, semicolon (";")
130 probably means something to the shell, so use quotation marks.
131 There is no way with this method to have different weights for differ‐
133 ent components of a pixel.
134 The -normalize option is often quite handy with -matrix because it lets
136 you quickly throw together the command without working out the math to
137 make sure the matrix isn't biased. Note that if you use the -normalize
138 option, the weights in the matrix aren't actually the numbers you spec‐
139 ify in the -matrix option.
140 Regular Matrix File
143 Specify the name of the matrix file with a -matrixfile option. Or
145 specify a list of them, one for each plane of the image.
146 Examples:
148 -matrixfile=mymatrix
150 -matrixfile=myred,mygreen,myblue
152 Each file applies to one plane of the image (e.g. red, green, or blue),
154 in order. The matrix in each file must have the same dimensions. If
155 the input image has more planes than the number of files you specify,
156 the first file applies to the extra planes as well.
157 pnmconvol interprets the file as text, with lines delimited by Unix
159 newline characters (line feeds).
160 Each line of the file is one row of the matrix, in order from top to
162 bottom.
163 For each row, the file contains a floating point decimal number for
165 each element in the row, from left to right, separated by spaces. This
166 is not just any old white space -- it is exactly one space. Two spaces
167 in a row mean you've specified a null string for an element (which is
168 invalid). If you want to line up your matrix visually, use leading and
169 trailing zeroes in the floating point numbers to do it.
170 There is no way to put comments in the file. There is no signature or
172 any other metadata in the file.
173 Note that if you use the -normalize option, the weights in the matrix
175 aren't actually what is in the file.
176 PNM File
179 Before Netpbm 10.49 (December 2009), this was the only way to specify a
181 convolution matrix. pnmconvol used this method in an attempt to
182 exploit the generic matrix processing capabilities of Netpbm, but as
183 the Netpbm formats don't directly allow matrices with the kinds of num‐
184 bers you need in a convolution matrix, it is quite cumbersome. In
185 fact, there simply is no way to specify some convolution matrices with
186 a legal Netpbm image, so to make it work, pnmconvol has to relax the
187 Netpbm file requirement that sample values be no greater than the
188 image's maxval. I.e. it isn't even a real PNM file.
189 The way you select this method of supplying the convolution matrix is
191 to not specify -matrix or -matrixfile. When you do that, you must
192 specify a second non-option argument -- that is the name of the PNM
193 file (or PNM equivalent PAM file).
194 There are two ways pnmconvol interprets the PNM convolution matrix
196 image pixels as weights: with offsets, and without offsets.
197 The simpler of the two is without offsets. That is what happens when
199 you specify the -nooffset option. In that case, pnmconvol simply nor‐
200 malizes the sample values in the PNM image by dividing by the maxval.
201 For example, here is a sample convolution file that causes an output
203 pixel to be a simple average of its corresponding input pixel and its 8
204 neighbors, resulting in a smoothed image:
205 P2
207 3 3
208 18
209 2 2 2
210 2 2 2
211 2 2 2
212 (Note that the above text is an actual PGM file -- you can cut and
214 paste it. If you're not familiar with the plain PGM format, see the
215 PGM format specification(1)).
216 pnmconvol divides each of the sample values (2) by the maxval (18) so
218 the weight of each of the 9 input pixels gets is 1/9, which is exactly
219 what you want to keep the overall brightness of the image the same.
220 pnmconvol creates an output pixel by multiplying the values of each of
221 9 pixels by 1/9 and adding.
222 Note that with maxval 18, the range of possible values is 0 to 18.
224 After scaling, the range is 0 to 1.
225 For a normal convolution, where you're neither adding nor subtracting
227 total value from the image, but merely moving it around, you'll want to
228 make sure that all the scaled values in (each plane of) your convolu‐
229 tion PNM add up to 1, which means all the actual sample values add up
230 to the maxval. Alternatively, you can use the -normalize option to
231 scale the scaled values further to make them all add up to 1 automati‐
232 cally.
233 When you don't specify -nooffset, pnmconvol applies an offset, the pur‐
235 pose of which is to allow you to indicate negative weights even though
236 PNM sample values are never negative. In this case, pnmconvol sub‐
237 tracts half the maxval from each sample and then normalizes by dividing
238 by half the maxval. So to get the same result as we did above with
239 -nooffset, the convolution matrix PNM image would have to look like
240 this:
241 P2
243 3 3
244 18
245 10 10 10
246 10 10 10
247 10 10 10
248 To see how this works, do the above-mentioned offset: 10 - 18/2 gives
250 1. The normalization step divides by 18/2 = 9, which makes it 1/9 -
251 exactly what you want. The equivalent matrix for 5x5 smoothing would
252 have maxval 50 and be filled with 26.
253 Note that with maxval 18, the range of possible values is 0 to 18.
255 After offset, that's -9 to 9, and after normalizing, the range is -1 to
256 1.
257 The convolution file will usually be a PGM, so that the same convolu‐
259 tion gets applied to each color component. However, if you want to use
260 a PPM and do a different convolution to different colors, you can cer‐
261 tainly do that.
262 Other Forms of Convolution
266 pnmconvol does only arithmetic, linear combination convolution. There
267 are other forms of convolution that are especially useful in image pro‐
268 cessing.
269 pgmmedian does median filtering, which is a form of convolution where
271 the output pixel value, rather than being a linear combination of the
272 pixels in the window, is the median of a certain subset of them.
273 pgmmorphconv does dilation and erosion, which is like the median filter
275 but the output value is the minimum or maximum of the values in the
276 window.
277
281 -matrix=convolution_matrix
282 The value of the convolution matrix. See Convolution Matrix
283 ⟨#matrixopt⟩ .
284 You may not specify both this and -matrixfile.
286 This option was new in Netpbm 10.49 (December 2009). Before
288 that, use a PNM file for the convolution matrix.
289 -matrixfile=filename
292 This specifies that you are supplying the convolution matrix in
293 a file and names that file. See Convolution Matrix
294 ⟨#matrixfile⟩ .
295 You may not specify both this and -matrix.
297 This option was new in Netpbm 10.49 (December 2009). Before
299 that, use a PNM file for the convolution matrix.
300 -normalize
303 This option says to adjust the weights in your convolution
304 matrix so they all add up to one. You usually want them to add
305 up to one so that the convolved result tends to have the same
306 overall brightness as the input. With -normalize, pnmconvol
307 scales all the weights by the same factor to make the sum one.
308 It does this for each plane.
309 This can be quite convenient because you can just throw numbers
311 into the matrix that have roughly the right relationship to each
312 other and let pnmconvol do the work of normalizing them. And
313 you can adjust a matrix by raising or lowering certain weights
314 without having to modify all the other weights to maintain nor‐
315 malcy. And you can use friendly integers.
316 Example:
318 $ pnmconvol myimage.ppm -normalize -matrix=1,1,1;1,1,1;1,1,1
320 This is of course a basic 3x3 average, but without you having to
322 specify 1/9 (.1111111) for each weight.
323 This option was new in Netpbm 10.50 (March 2010). But before
325 Netpbm 10.79 (June 2017), it has no effect when you specify the
326 convolution matrix via pseudo-PNM file.
327 -bias=n
330 This specifies an amount to add to the convolved value for each
332 sample.
333 The purpose of this addition is normally to handle negative con‐
335 volution results. Because the convolution matrix can contain
336 negative numbers, the convolved value for a pixel could be nega‐
337 tive. But Netpbm formats cannot contain negative sample values,
338 so without any bias, such samples would get clipped to zero.
339 The bias allows the output image to retain the information, and
340 a program that pocesses that output, knowing the bias value,
341 could reconstruct the real convolved values.
342 For example, with bias=100, a sample whose convolved value is -5
344 appears as 95 in the output, whereas a sample whose convolved
345 value is 5 appears as 105 in the output.
346 A typical value for the bias is half the maxval, allowing the
348 same range on either side of zero.
349 If the sample value, after adding the bias, is still less than
351 zero, pnmconvol clips it to zero. If it exceeds the maxval of
352 the output image, it clips it to the maxval.
353 The default is zero.
355 This option was new in Netpbm 10.68 (September 2014).
357 -nooffset=
360 This is part of the obsolete PNM image method of specifying the
361 convolution matrix. See Convolution Matrix ⟨#matrixpnm⟩ .
362
368 The -nooffset option was new in Netpbm 10.23 (July 2004), making it
369 substantially easier to specify a convolution matrix, but still hard.
370 In Netpbm 10.49 (December 2009), the PNM convolution matrix tyranny was
371 finally ended with the -matrix and -matrixfile options. In between,
372 pnmconvol was broken for a while because the Netpbm library started
373 enforcing the requirement that a sample value not exceed the maxval of
374 the image. pnmconvol used the Netpbm library to read the PNM convolu‐
375 tion matrix file, but in the pseudo-PNM format that pnmconvol uses, a
376 sample value sometimes has to exceed the maxval.
377
381 pnmsmooth(1), pgmmorphconv(1), pgmmedian(1), pnmnlfilt(1), pgmker‐
382 nel(1), pamgauss(1), pammasksharpen(1), pnmpad(1), pamcut(1), pnm(1)
383
386 Copyright (C) 1989, 1991 by Jef Poskanzer. Modified 26 November 1994
387 by Mike Burns, burns@chem.psu.edu
388
390 This manual page was generated by the Netpbm tool 'makeman' from HTML
391 source. The master documentation is at
392 http://netpbm.sourceforge.net/doc/pnmconvol.html
394netpbm documentation 30 November 2018 Pnmconvol User Manual(0)