Provided by: mia-tools_2.4.6-5build3_amd64 
NAME
mia-2dcost - Evaluate the similarity between two 2D images.
SYNOPSIS
mia-2dcost [options] <PLUGINS:2dimage/fullcost>
DESCRIPTION
mia-2dcost This program is used to evaluate the cost between two images by using a given cost function.
OPTIONS
Help & Info
-V --verbose=warning
verbosity of output, print messages of given level and higher priorities. Supported
priorities starting at lowest level are:
trace ‐ Function call trace
debug ‐ Debug output
info ‐ Low level messages
message ‐ Normal messages
warning ‐ Warnings
fail ‐ Report test failures
error ‐ Report errors
fatal ‐ Report only fatal errors
--copyright
print copyright information
-h --help
print this help
-? --usage
print a short help
--version
print the version number and exit
Processing
--threads=-1
Maxiumum number of threads to use for processing,This number should be lower or equal to
the number of logical processor cores in the machine. (-1: automatic estimation).
PLUGINS: 1d/splinekernel
bspline B-spline kernel creation , supported parameters are:
d = 3; int in [0, 5]
Spline degree.
omoms OMoms-spline kernel creation, supported parameters are:
d = 3; int in [3, 3]
Spline degree.
PLUGINS: 2dimage/cost
lncc local normalized cross correlation with masking support., supported parameters are:
w = 5; uint in [1, 256]
half width of the window used for evaluating the localized cross correlation.
lsd Least-Squares Distance measure
(no parameters)
mi Spline parzen based mutual information., supported parameters are:
cut = 0; float in [0, 40]
Percentage of pixels to cut at high and low intensities to remove outliers.
mbins = 64; uint in [1, 256]
Number of histogram bins used for the moving image.
mkernel = [bspline:d=3]; factory
Spline kernel for moving image parzen hinstogram. For supported plug-ins see
PLUGINS:1d/splinekernel
rbins = 64; uint in [1, 256]
Number of histogram bins used for the reference image.
rkernel = [bspline:d=0]; factory
Spline kernel for reference image parzen hinstogram. For supported plug-ins see
PLUGINS:1d/splinekernel
ncc normalized cross correlation.
(no parameters)
ngf This function evaluates the image similarity based on normalized gradient fields. Various
evaluation kernels are available., supported parameters are:
eval = ds; dict
plugin subtype. Supported values are:
sq ‐ square of difference
ds ‐ square of scaled difference
dot ‐ scalar product kernel
cross ‐ cross product kernel
ssd 2D imaga cost: sum of squared differences, supported parameters are:
autothresh = 0; float in [0, 1000]
Use automatic masking of the moving image by only takeing intensity values into accound
that are larger than the given threshold.
norm = 0; bool
Set whether the metric should be normalized by the number of image pixels.
ssd-automask
2D image cost: sum of squared differences, with automasking based on given thresholds,
supported parameters are:
rthresh = 0; double
Threshold intensity value for reference image.
sthresh = 0; double
Threshold intensity value for source image.
PLUGINS: 2dimage/fullcost
image Generalized image similarity cost function that also handles multi-resolution processing. The
actual similarity measure is given es extra parameter., supported parameters are:
cost = ssd; factory
Cost function kernel. For supported plug-ins see PLUGINS:2dimage/cost
debug = 0; bool
Save intermediate resuts for debugging.
ref =(input, io)
Reference image. For supported file types see PLUGINS:2dimage/io
src =(input, io)
Study image. For supported file types see PLUGINS:2dimage/io
weight = 1; float
weight of cost function.
labelimage
Similarity cost function that maps labels of two images and handles label-preserving multi-
resolution processing., supported parameters are:
debug = 0; int in [0, 1]
write the distance transforms to a 3D image.
maxlabel = 256; int in [2, 32000]
maximum number of labels to consider.
ref =(input, io)
Reference image. For supported file types see PLUGINS:2dimage/io
src =(input, io)
Study image. For supported file types see PLUGINS:2dimage/io
weight = 1; float
weight of cost function.
maskedimage
Generalized masked image similarity cost function that also handles multi-resolution
processing. The provided masks should be densly filled regions in multi-resolution procesing
because otherwise the mask information may get lost when downscaling the image. The reference
mask and the transformed mask of the study image are combined by binary AND. The actual
similarity measure is given es extra parameter., supported parameters are:
cost = ssd; factory
Cost function kernel. For supported plug-ins see PLUGINS:2dimage/maskedcost
ref =(input, io)
Reference image. For supported file types see PLUGINS:2dimage/io
ref-mask =(input, io)
Reference image mask (binary). For supported file types see PLUGINS:2dimage/io
src =(input, io)
Study image. For supported file types see PLUGINS:2dimage/io
src-mask =(input, io)
Study image mask (binary). For supported file types see PLUGINS:2dimage/io
weight = 1; float
weight of cost function.
PLUGINS: 2dimage/io
bmp BMP 2D-image input/output support. The plug-in supports reading and writing of binary images
and 8-bit gray scale images. read-only support is provided for 4-bit gray scale images. The
color table is ignored and the pixel values are taken as literal gray scale values.
Recognized file extensions: .BMP, .bmp
Supported element types:
binary data, unsigned 8 bit
datapool Virtual IO to and from the internal data pool
Recognized file extensions: .@
dicom 2D image io for DICOM
Recognized file extensions: .DCM, .dcm
Supported element types:
signed 16 bit, unsigned 16 bit
exr a 2dimage io plugin for OpenEXR images
Recognized file extensions: .EXR, .exr
Supported element types:
unsigned 32 bit, floating point 32 bit
jpg a 2dimage io plugin for jpeg gray scale images
Recognized file extensions: .JPEG, .JPG, .jpeg, .jpg
Supported element types:
unsigned 8 bit
png a 2dimage io plugin for png images
Recognized file extensions: .PNG, .png
Supported element types:
binary data, unsigned 8 bit, unsigned 16 bit
raw RAW 2D-image output support
Recognized file extensions: .RAW, .raw
Supported element types:
binary data, signed 8 bit, unsigned 8 bit, signed 16 bit, unsigned 16 bit, signed 32 bit,
unsigned 32 bit, floating point 32 bit, floating point 64 bit
tif TIFF 2D-image input/output support
Recognized file extensions: .TIF, .TIFF, .tif, .tiff
Supported element types:
binary data, unsigned 8 bit, unsigned 16 bit, unsigned 32 bit
vista a 2dimage io plugin for vista images
Recognized file extensions: .-, .V, .VISTA, .v, .vista
Supported element types:
binary data, signed 8 bit, unsigned 8 bit, signed 16 bit, unsigned 16 bit, signed 32 bit,
unsigned 32 bit, floating point 32 bit, floating point 64 bit
PLUGINS: 2dimage/maskedcost
lncc local normalized cross correlation with masking support., supported parameters are:
w = 5; uint in [1, 256]
half width of the window used for evaluating the localized cross correlation.
mi Spline parzen based mutual information with masking., supported parameters are:
cut = 0; float in [0, 40]
Percentage of pixels to cut at high and low intensities to remove outliers.
mbins = 64; uint in [1, 256]
Number of histogram bins used for the moving image.
mkernel = [bspline:d=3]; factory
Spline kernel for moving image parzen hinstogram. For supported plug-ins see
PLUGINS:1d/splinekernel
rbins = 64; uint in [1, 256]
Number of histogram bins used for the reference image.
rkernel = [bspline:d=0]; factory
Spline kernel for reference image parzen hinstogram. For supported plug-ins see
PLUGINS:1d/splinekernel
ncc normalized cross correlation with masking support.
(no parameters)
ssd Sum of squared differences with masking.
(no parameters)
EXAMPLE
Evaluate the SSD cost function between image1.png and image2.png
mia-2dcost image:src=image1.png,ref=image2.png,cost=ssd
AUTHOR(s)
Gert Wollny
COPYRIGHT
This software is Copyright (c) 1999‐2015 Leipzig, Germany and Madrid, Spain. It comes with ABSOLUTELY
NO WARRANTY and you may redistribute it under the terms of the GNU GENERAL PUBLIC LICENSE Version 3
(or later). For more information run the program with the option '--copyright'.