Pnmnlfilt User Manual(1) General Commands Manual Pnmnlfilt User Manual(1)
NAME
pnmnlfilt - non-linear filters: smooth, alpha trim mean, optimal estima-
tion smoothing, edge enhancement.
SYNOPSIS
pnmnlfilt alpha radius [pnmfile]
DESCRIPTION
This program is part of Netpbm(1).
pnmnlfilt produces an output image where the pixels are a summary of
multiple pixels near the corresponding location in an input image.
This program works on multi-image streams.
This is something of a swiss army knife filter. It has 3 distinct oper-
ating modes. In all of the modes pnmnlfilt 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), pn-
mnlfilt 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 hexa-
gons essentially fit into the subject pixel (ie. there will be no fil-
tering effect). A radius value of 1.0 means that the 7 hexagons essen-
tially cover the 3x3 immediate neighbor square.
Your choice of "alpha" parameter selects among the three modes.
Alpha trimmed mean filter (0.0 <= alpha <= 0.5)
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 bot-
tom 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 de-
termine 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 ef-
fect, try alpha 0.0 and radius 1.0
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 val-
ues 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
Optimal estimation smoothing. (1.0 <= alpha <= 2.0)
This type of filter applies a smoothing filter adaptively over the im-
age. 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 ra-
dius, 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.
Edge enhancement. (-0.1 >= alpha >= -0.9)
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 ef-
fective radius as usual, but useful values are between 0.5 and 0.9. Try
starting with values of alpha = 0.3, radius = 0.8
Combination use.
The various modes of pnmnlfilt 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.
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. Sev-
eral 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.
OPTIONS
There are no command line options defined specifically for pnmnlfilt,
but it recognizes the options common to all programs based on libnetpbm
(See ]8;;index.html#commonoptions\ Common Options]8;;\ .)
REFERENCES
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 en-
hanced to allow continuous alpha adjustment.
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.
The edge enhancement details are from pgmenhance(1), 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.
PARAMETERS
The parameters are:
alpha The alpha value (described above), in decimal. May be frac-
tional.
radius The radius (described above), in decimal. May be fractional.
SEE ALSO
pgmenhance(1), pnmconvol(1), pnm(1)
AUTHOR
Graeme W. Gill graeme@labtam.oz.au
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/pnmnlfilt.html
netpbm documentation 24 October 2006 Pnmnlfilt User Manual(1)
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