Adding upstream version 4.22.0.upstream/4.22.0

Signed-off-by: Daniel Baumann <daniel.baumann@progress-linux.org>

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+\
+.\" This man page was generated by the Netpbm tool 'makeman' from HTML source.
+.\" Do not hand-hack it!  If you have bug fixes or improvements, please find
+.\" the corresponding HTML page on the Netpbm website, generate a patch
+.\" against that, and send it to the Netpbm maintainer.
+.TH "Pnmnlfilt User Manual" 0 "24 October 2006" "netpbm documentation"
+
+.SH NAME
+
+pnmnlfilt - non-linear filters: smooth, alpha trim mean, optimal
+estimation smoothing, edge enhancement.
+
+.UN synopsis
+.SH SYNOPSIS
+
+\fBpnmnlfilt\fP
+\fIalpha\fP
+\fIradius\fP
+[\fIpnmfile\fP]
+
+.UN description
+.SH DESCRIPTION
+.PP
+This program is part of
+.BR "Netpbm" (1)\c
+\&.
+.PP
+\fBpnmnlfilt\fP produces an output image where the pixels are a
+summary of multiple pixels near the corresponding location in an input
+image.
+.PP
+This program works on multi-image streams.
+.PP
+This is something of a swiss army knife filter.  It has 3 distinct
+operating modes.  In all of the modes \fBpnmnlfilt\fP examines each
+pixel in the image and processes it according to the values of it and
+its surrounding pixels.  Rather than using a square block of
+surrounding pixels (e.g. the subject pixel and its 8 immediate
+neighbors, in a 3x3 square), \fBpnmnlfilt\fP uses 7 hexagonal areas.
+You choose the size of the hexagons with the radius parameter.  A
+radius value of 1/3 means that the 7 hexagons essentially fit into the
+subject pixel (ie.  there will be no filtering effect).  A radius
+value of 1.0 means that the 7 hexagons essentially cover the 3x3
+immediate neighbor square.
+.PP
+Your choice of "alpha" parameter selects among the three
+modes.
+
+.UN alphatrimmedmean
+.SS 
+Alpha trimmed mean filter (0.0 <= alpha <= 0.5)
+.PP
+The value of the center pixel will be replaced by the mean of
+the 7 hexagon values, but the 7 values are sorted by size and the top
+and bottom alpha portion of the 7 are excluded from the mean.  This
+implies that an alpha value of 0.0 gives the same sort of output as a
+normal convolution (ie. averaging or smoothing filter), where radius
+will determine the "strength" of the filter. A good value to
+start from for subtle filtering is alpha = 0.0, radius = 0.55 For a
+more blatant effect, try alpha 0.0 and radius 1.0
+.PP
+An alpha value of 0.5 will cause the median value of the 7 hexagons
+to be used to replace the center pixel value. This sort of filter is
+good for eliminating "pop" or single pixel noise from an
+image without spreading the noise out or smudging features on the
+image. Judicious use of the radius parameter will fine tune the
+filtering. Intermediate values of alpha give effects somewhere between
+smoothing and "pop" noise reduction. For subtle filtering
+try starting with values of alpha = 0.4, radius = 0.6 For a more
+blatant effect try alpha = 0.5, radius = 1.0
+
+.UN optimalestsmooth
+.SS 
+Optimal estimation smoothing. (1.0 <= alpha <= 2.0)
+.PP
+This type of filter applies a smoothing filter adaptively over the
+image.  For each pixel the variance of the surrounding hexagon values
+is calculated, and the amount of smoothing is made inversely
+proportional to it. The idea is that if the variance is small then it
+is due to noise in the image, while if the variance is large, it is
+because of "wanted" image features. As usual the radius
+parameter controls the effective radius, but it probably advisable to
+leave the radius between 0.8 and 1.0 for the variance calculation to
+be meaningful.  The alpha parameter sets the noise threshold, over
+which less smoothing will be done.  This means that small values of
+alpha will give the most subtle filtering effect, while large values
+will tend to smooth all parts of the image. You could start with
+values like alpha = 1.2, radius = 1.0 and try increasing or decreasing
+the alpha parameter to get the desired effect. This type of filter is
+best for filtering out dithering noise in both bitmap and color
+images.
+
+.UN edgeenhance
+.SS Edge enhancement. (-0.1 >= alpha >= -0.9)
+.PP
+This is the opposite type of filter to the smoothing filter. It
+enhances edges. The alpha parameter controls the amount of edge
+enhancement, from subtle (-0.1) to blatant (-0.9). The radius
+parameter controls the effective radius as usual, but useful values
+are between 0.5 and 0.9. Try starting with values of alpha = 0.3,
+radius = 0.8
+
+.UN combination
+.SS Combination use.
+.PP
+The various modes of \fBpnmnlfilt\fP can be used one after the
+other to get the desired result. For instance to turn a monochrome
+dithered image into a grayscale image you could try one or two passes
+of the smoothing filter, followed by a pass of the optimal estimation
+filter, then some subtle edge enhancement. Note that using edge
+enhancement is only likely to be useful after one of the non-linear
+filters (alpha trimmed mean or optimal estimation filter), as edge
+enhancement is the direct opposite of smoothing.
+.PP
+For reducing color quantization noise in images (ie. turning .gif
+files back into 24 bit files) you could try a pass of the optimal
+estimation filter (alpha 1.2, radius 1.0), a pass of the median filter
+(alpha 0.5, radius 0.55), and possibly a pass of the edge enhancement
+filter.  Several passes of the optimal estimation filter with
+declining alpha values are more effective than a single pass with a
+large alpha value.  As usual, there is a tradeoff between filtering
+effectiveness and losing detail. Experimentation is encouraged.
+
+.UN references
+.SH References:
+.PP
+The alpha-trimmed mean filter is based on the description in IEEE
+CG&A May 1990 Page 23 by Mark E. Lee and Richard A. Redner, and
+has been enhanced to allow continuous alpha adjustment.
+.PP
+The optimal estimation filter is taken from an article
+"Converting Dithered Images Back to Gray Scale" by Allen
+Stenger, Dr Dobb's Journal, November 1992, and this article references
+"Digital Image Enhancement and Noise Filtering by Use of Local
+Statistics", Jong-Sen Lee, IEEE Transactions on Pattern Analysis
+and Machine Intelligence, March 1980.
+.PP
+The edge enhancement details are from
+.BR "pgmenhance" (1)\c
+\&, which is taken from Philip
+R. Thompson's "xim" program, which in turn took it from
+section 6 of "Digital Halftones by Dot Diffusion",
+D. E. Knuth, ACM Transaction on Graphics Vol. 6, No. 4, October 1987,
+which in turn got it from two 1976 papers by J. F. Jarvis et. al.
+
+.UN parameters
+.SH 
+.PP
+The parameters are:
+
+
+.TP
+\fIalpha\fP
+The alpha value (described above), in decimal.  May be fractional.
+
+.TP
+\fIradius\fP
+The radius (described above), in decimal.  May be fractional.
+
+
+.UN seealso
+.SH SEE ALSO
+.BR "pgmenhance" (1)\c
+\&,
+.BR "pnmconvol" (1)\c
+\&,
+.BR "pnm" (5)\c
+\&
+
+.UN author
+.SH AUTHOR
+
+Graeme W. Gill \fIgraeme@labtam.oz.au\fP
+.SH DOCUMENT SOURCE
+This manual page was generated by the Netpbm tool 'makeman' from HTML
+source.  The master documentation is at
+.IP
+.B http://netpbm.sourceforge.net/doc/pnmnlfilt.html
+.PP
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