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.TH densnorm 1 4.6.34 IMOD
.SH NAME
densnorm - Normalize densities in an image file
.SH SYNOPSIS
densnorm [options] [Input_file] [Output_file]
.SH DESCRIPTION
Densnorm can normalize images by dividing by the incident illumination, an
operation usually referred to as mass normalization. It can take the log of
normalized data, or simply take the log of the input data. It can also
output weighting factors that can be supplied to Tilt(1) to provide a
relative normalization of the data, thus avoiding the need to write a
normalized file.
.P
Mass normalization is done in order to bring different images to a common
scale so that they all represent projections of the same structure. That
way, images at different angles will be appropriately weighted in a
backprojection. A relative normalization, where images are just adjusted for
different exposures, is sufficient for this purpose. An absolute
normalization is useful if one wants images that are proportional to the sum
of the mass densities in the specimen, with no additive constants. Absolute
normalization requires information about the image intensity that would be
produced by the unattenuated beam. With this information, the program can
compute a transmittance value, I/I0, where I is the image intensity at each
pixel and I0 is the intensity produced by the unattenuated beam.
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The treatment of transmittance values depends on whether the log is going to
be taken of the data. This choice would depend on the source of contrast.
For stained samples where amplitude contrast dominates, the projected mass
density should be proportion to the negative of the log of the
transmittance. In this case, taking the log of the transmittance is
appropriate and will result in negative values, where 0 corresponds to 0
projected mass. When phase contrast dominates, it seems that the amount of
attenuation of the beam should be proportional to the linear sum of mass
densities. Here, it should be appropriate not to take the log. Thus, when
the log is not being taken, the program will express the densities as
attenuations by taking one minus the transmittance (1 - I/I0). These
attenuations will also be negative numbers, with 0 corresponding to 0 mass.
In either case, you can convert the negative values to positive ones, but
this will reverse the contrast of the data and make density appear white.
.P
Standard R-weighted backprojection as implemented in Tilt(1) is insensitive
to the mean value of images, and there is no value in having an absolute
normalization. On the other hand, having density values where 0 means 0
mass is potentially important for algebraic reconstruction techniques, where
it is possible to constrain values to be all positive or all negative.
These considerations motivate the following recommendations for various
cases:
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1) R-weighted back projection when taking the log: Do not bother to normalize
the data; it should have no effect.
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2) R-weighted back projection when not taking the log: A relative
normalization is sufficient; use this program either to normalize the data
or to compute weighting factors to pass to Tilt(1).
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3) Algebraic technique without zero constraints, and taking the log:
Normalization is unnecessary but use this program to take the log before
starting the reconstruction procedure.
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4) Algebraic technique without zero constraints, and without taking the
log: A relative normalization is sufficient; as in 2), either normalize the
data or pass weighting factors to Tilt(1) (assuming Tilt(1) will be involved
in the algebraic technique).
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5) Algebraic technique with zero constraints, and taking the log: An
absolute normalization is needed, using reference image data; take the log
after normalizing.
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6) Algebraic technique with zero constraints, and without taking the log: An
absolute normalization is needed.
.SH OPTIONS
Densnorm uses the PIP package for input exclusively (see the manual page for
pip(1)). The following options can be specified either as command line
arguments (with the -) or one per line in a command file or parameter file
(without the -). Options can be abbreviated to unique letters; the
currently valid abbreviations for short names are shown in parentheses.
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INSERT OPTION TEXT HERE
.TP
.B -StandardInput
Read parameter entries from standard input.
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.SH HISTORY
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Written by David Mastronarde, 7/16/07
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.SH BUGS
Email bug reports to mast@colorado.edu.