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 Convolution means replacing each pixel with a weighted average of the
31 nearby pixels. The weights and the area to average are determined by
32 the convolution matrix (sometimes called a convolution kernel), which
33 you supply in one of several ways. See
34 Convolution Matrix ⟨#convolutionmatrix⟩ .
35 At the edges of the convolved image, where the convolution matrix would
37 extend over the edge of the image, pnmconvol just copies the input pix‐
38 els directly to the output. It's often better to deal with the pixels
39 near an edge by assuming some blank or background color beyond the
40 edge. To do that, use pnmpad to add a margin all around whose size is
41 half that of your convolution matrix size, not counting its center, in
42 the same dimension. (E.g. if your convolution matrix is 5 wide by 3
43 high, use pnmpad -left=2 -right=2 -top=1 -bottom=1). Feed that
44 enlarged image to pnmconvol, then use pamcut to chop the edges off the
45 convolved output, getting back to your original image dimensions.
46 (E.g. pamcut -left=2 -right=-2 -top=1 -bottom=-1).
47 The convolution computation can result in a value which is outside the
49 range representable in the output. When that happens, pnmconvol just
50 clips the output, which means brightness is not conserved.
51 To avoid clipping, you may want to scale your input values. For exam‐
53 ple, if your convolution matrix might produce an output value as much
54 as double the maximum value in the input, then make sure the maxval of
55 the input (which is also the maxval of the output) is at least twice
56 the actual maximum value in the input.
57 Clipping negative numbers deserves special consideration. If your con‐
59 volution matrix includes negative numbers, it is possible for pnmconvol
60 to calculate an output pixel as a negative value, which pnmconvol would
61 of course clip to zero, since Netpbm formats cannot represent negative
62 numbers.
63 Convolution Matrix
67 There are three ways to specify the convolution matrix:
68 · directly with a -matrix option.
72 · In a file (or set of them) named by a -matrixfile option, whose
75 contents are similar to a -matrix option value.
76 · With a special PNM file.
79 The PNM file option is the hardest, and exists only because until
82 Netpbm 10.49 (December 2009), it was the only way.
83 The regular convolution matrix file is slightly easier to read than the
85 -matrix option value, and makes your command line less messy, but
86 requires you to manage a separate file. With the file, you can have
87 separate convolution matrices for the individual color components,
88 which you can't do with -matrix.
89 In any case, the convolution matrix pnmconvol uses is a matrix of real
91 numbers. They can be whole or fractional, positive, negative, or zero.
92 The convolution matrix always has an odd width and height, so that
94 there is a center element. pnmconvol figuratively places that center
95 element over a pixel of the input image and weights that pixel and its
96 neighbors as indicated by the convolution matrix to produce the pixel
97 in the same location of the output image.
98 For a normal convolution, where you're neither adding nor subtracting
100 total value from the image, but merely moving it around, you'll want to
101 make sure that all the numbers in the matrix add up to 1. If they
102 don't, pnmconvol warns you.
103 The elements of the matrix are actually tuples, one for each sample in
105 the input. (I.e. if the input is an RGB image, each element of the
106 convolution matrix has one weight for red, one for green, and one for
107 blue.
108 Directly On the Command Line
111 Here are examples of a -matrix option:
113 -matrix=0,.2,0;.2,.2,.2;0,.2,0
115 -matrix=-1,3,-1
117 The value consists of each row of the matrix from top to bottom, sepa‐
119 rated by semicolons. Each row consists of the elements of the row from
120 left to right, separated by commas. You must of course have the same
121 number of elements in each row. Each element is a decimal floating
122 point number and is the weight to give to each component of a pixel
123 that corresponds to that matrix location.
124 Note that when you supply this option via a shell, semicolon (";")
126 probably means something to the shell, so use quotation marks.
127 There is no way with this method to have different weights for differ‐
129 ent components of a pixel.
130 The -normalize option is often quite handy with -matrix because it lets
132 you quickly throw together the command without working out the math to
133 make sure the matrix isn't biased. Note that if you use the -normalize
134 option, the weights in the matrix aren't actually the numbers you spec‐
135 ify in the -matrix option.
136 Regular Matrix File
139 Specify the name of the matrix file with a -matrixfile option. Or
141 specify a list of them, one for each plane of the image.
142 Examples:
144 -matrixfile=mymatrix
146 -matrixfile=myred,mygreen,myblue
148 Each file applies to one plane of the image (e.g. red, green, or blue),
150 in order. The matrix in each file must have the same dimensions. If
151 the input image has more planes than the number of files you specify,
152 the first file applies to the extra planes as well.
153 pnmconvol interprets the file as text, with lines delimited by Unix
155 newline characters (line feeds).
156 Each line of the file is one row of the matrix, in order from top to
158 bottom.
159 For each row, the file contains a floating point decimal number for
161 each element in the row, from left to right, separated by spaces. This
162 is not just any old white space -- it is exactly one space. Two spaces
163 in a row mean you've specified a null string for an element (which is
164 invalid). If you want to line up your matrix visually, use leading and
165 trailing zeroes in the floating point numbers to do it.
166 There is no way to put comments in the file. There is no signature or
168 any other metadata in the file.
169 Note that if you use the -normalize option, the weights in the matrix
171 aren't actually what is in the file.
172 PNM File
175 Before Netpbm 10.49 (December 2009), this was the only way to specify a
177 convolution matrix. pnmconvol used this method in an attempt to
178 exploit the generic matrix processing capabilities of Netpbm, but as
179 the Netpbm formats don't directly allow matrices with the kinds of num‐
180 bers you need in a convolution matrix, it is quite cumbersome. In
181 fact, there simply is no way to specify some convolution matrices with
182 a legal Netpbm image, so to make it work, pnmconvol has to relax the
183 Netpbm file requirement that sample values be no greater than the
184 image's maxval. I.e. it isn't even a real PNM file.
185 The way you select this method of supplying the convolution matrix is
187 to not specify -matrix or -matrixfile. When you do that, you must
188 specify a second non-option argument -- that is the name of the PNM
189 file (or PNM equivalent PAM file).
190 There are two ways pnmconvol interprets the PNM convolution matrix
192 image pixels as weights: with offsets, and without offsets.
193 The simpler of the two is without offsets. That is what happens when
195 you specify the -nooffset option. In that case, pnmconvol simply nor‐
196 malizes the sample values in the PNM image by dividing by the maxval.
197 For example, here is a sample convolution file that causes an output
199 pixel to be a simple average of its corresponding input pixel and its 8
200 neighbors, resulting in a smoothed image:
201 P2
203 3 3
204 18
205 2 2 2
206 2 2 2
207 2 2 2
208 (Note that the above text is an actual PGM file -- you can cut and
210 paste it. If you're not familiar with the plain PGM format, see the
211 PGM format specification(1)).
212 pnmconvol divides each of the sample values (2) by the maxval (18) so
214 the weight of each of the 9 input pixels gets is 1/9, which is exactly
215 what you want to keep the overall brightness of the image the same.
216 pnmconvol creates an output pixel by multiplying the values of each of
217 9 pixels by 1/9 and adding.
218 Note that with maxval 18, the range of possible values is 0 to 18.
220 After scaling, the range is 0 to 1.
221 For a normal convolution, where you're neither adding nor subtracting
223 total value from the image, but merely moving it around, you'll want to
224 make sure that all the scaled values in (each plane of) your convolu‐
225 tion PNM add up to 1, which means all the actual sample values add up
226 to the maxval. Alternatively, you can use the -normalize option to
227 scale the scaled values further to make them all add up to 1 automati‐
228 cally.
229 When you don't specify -nooffset, pnmconvol applies an offset, the pur‐
231 pose of which is to allow you to indicate negative weights even though
232 PNM sample values are never negative. In this case, pnmconvol sub‐
233 tracts half the maxval from each sample and then normalizes by dividing
234 by half the maxval. So to get the same result as we did above with
235 -nooffset, the convolution matrix PNM image would have to look like
236 this:
237 P2
239 3 3
240 18
241 10 10 10
242 10 10 10
243 10 10 10
244 To see how this works, do the above-mentioned offset: 10 - 18/2 gives
246 1. The normalization step divides by 18/2 = 9, which makes it 1/9 -
247 exactly what you want. The equivalent matrix for 5x5 smoothing would
248 have maxval 50 and be filled with 26.
249 Note that with maxval 18, the range of possible values is 0 to 18.
251 After offset, that's -9 to 9, and after normalizing, the range is -1 to
252 1.
253 The convolution file will usually be a PGM, so that the same convolu‐
255 tion gets applied to each color component. However, if you want to use
256 a PPM and do a different convolution to different colors, you can cer‐
257 tainly do that.
258 Other Forms of Convolution
262 pnmconvol does only arithmetic, linear combination convolution. There
263 are other forms of convolution that are especially useful in image pro‐
264 cessing.
265 pgmmedian does median filtering, which is a form of convolution where
267 the output pixel value, rather than being a linear combination of the
268 pixels in the window, is the median of a certain subset of them.
269 pgmmorphconv does dilation and erosion, which is like the median filter
271 but the output value is the minimum or maximum of the values in the
272 window.
273
277 -matrix=convolution_matrix
278 The value of the convolution matrix. See Convolution Matrix
279 ⟨#matrixopt⟩ .
280 You may not specify both this and -matrixfile.
282 This option was new in Netpbm 10.49 (December 2009). Before
284 that, use a PNM file for the convolution matrix.
285 -matrixfile=filename
288 This specifies that you are supplying the convolution matrix in
289 a file and names that file. See Convolution Matrix
290 ⟨#matrixfile⟩ .
291 You may not specify both this and -matrix.
293 This option was new in Netpbm 10.49 (December 2009). Before
295 that, use a PNM file for the convolution matrix.
296 -normalize
299 This option says to adjust the weights in your convolution
300 matrix so they all add up to one. You usually want them to add
301 up to one so that the convolved result tends to have the same
302 overall brightness as the input. With -normalize, pnmconvol
303 scales all the weights by the same factor to make the sum one.
304 It does this for each plane.
305 This can be quite convenient because you can just throw numbers
307 into the matrix that have roughly the right relationship to each
308 other and let pnmconvol do the work of normalizing them. And
309 you can adjust a matrix by raising or lowering certain weights
310 without having to modify all the other weights to maintain nor‐
311 malcy. And you can use friendly integers.
312 Example:
314 $ pnmconvol myimage.ppm -normalize -matrix=1,1,1;1,1,1;1,1,1
316 This is of course a basic 3x3 average, but without you having to
318 specify 1/9 (.1111111) for each weight.
319 This option was new in Netpbm 10.50 (March 2010). But before
321 Netpbm 10.79 (June 2017), it has no effect when you specify the
322 convolution matrix via pseudo-PNM file.
323 -bias=n
326 This specifies an amount to add to the convolved value for each
328 sample.
329 The purpose of this addition is normally to handle negative con‐
331 volution results. Because the convolution matrix can contain
332 negative numbers, the convolved value for a pixel could be nega‐
333 tive. But Netpbm formats cannot contain negative sample values,
334 so without any bias, such samples would get clipped to zero.
335 The bias allows the output image to retain the information, and
336 a program that pocesses that output, knowing the bias value,
337 could reconstruct the real convolved values.
338 For example, with bias=100, a sample whose convolved value is -5
340 appears as 95 in the output, whereas a sample whose convolved
341 value is 5 appears as 105 in the output.
342 A typical value for the bias is half the maxval, allowing the
344 same range on either side of zero.
345 If the sample value, after adding the bias, is still less than
347 zero, pnmconvol clips it to zero. If it exceeds the maxval of
348 the output image, it clips it to the maxval.
349 The default is zero.
351 This option was new in Netpbm 10.68 (September 2014).
353 -nooffset=
356 This is part of the obsolete PNM image method of specifying the
357 convolution matrix. See Convolution Matrix ⟨#matrixpnm⟩ .
358
363 The -nooffset option was new in Netpbm 10.23 (July 2004), making it
364 substantially easier to specify a convolution matrix, but still hard.
365 In Netpbm 10.49 (December 2009), the PNM convolution matrix tyranny was
366 finally ended with the -matrix and -matrixfile options. In between,
367 pnmconvol was broken for a while because the Netpbm library started
368 enforcing the requirement that a sample value not exceed the maxval of
369 the image. pnmconvol used the Netpbm library to read the PNM convolu‐
370 tion matrix file, but in the pseudo-PNM format that pnmconvol uses, a
371 sample value sometimes has to exceed the maxval.
372
376 pnmsmooth(1), pgmmorphconv(1), pgmmedian(1), pnmnlfilt(1), pgmker‐
377 nel(1), pamgauss(1), pammasksharpen(1), pnmpad(1), pamcut(1), pnm(1)
378
381 Copyright (C) 1989, 1991 by Jef Poskanzer. Modified 26 November 1994
382 by Mike Burns, burns@chem.psu.edu
383
385 This manual page was generated by the Netpbm tool 'makeman' from HTML
386 source. The master documentation is at
387 http://netpbm.sourceforge.net/doc/pnmconvol.html
389netpbm documentation 30 April 2017 Pnmconvol User Manual(0)