mia-2dimageregistration

Sysnopis:

mia-2dimageregistration {-i io} {-r io} {-t io} [ options ...] [ Plugin type: 2dimage/fullcost ...]

Description:

This program runs registration of two images optimizing a transformation of the given transformation model by optimizing certain cost measures that are given as free parameters.

Options:

File-IO

-i, --in-image=(input, required); io

test image to be registered. For supported file types see Plugin type: 2dimage/io

-r, --ref-image=(input, required); io

reference image to be registered to. For supported file types see Plugin type: 2dimage/io

-o, --out-image=(output); io

registered output image. For supported file types see Plugin type: 2dimage/io

-t, --transformation=(output, required); io

output transformation comprising the registration. For supported file types see Plugin type: 2dtransform/io

Help & Info

-V, --verbose=warning; dict

verbosity of output, print messages of given level and higher priorities. Supported priorities starting at lowest level are:

info:Low level messages
trace:Function call trace
fail:Report test failures
warning:Warnings
error:Report errors
debug:Debug output
message:Normal messages
fatal:Report only fatal errors
--copyright=(); bool

print copyright information

-h, --help=(); bool

print this help

-?, --usage=(); bool

print a short help

--version=(); bool

print the version number and exit

Parameters

-l, --levels=3; ulong

multi-resolution levels

-O, --optimizer=gsl:opt=gd,step=0.1; factory

Optimizer used for minimization. For supported plug-ins see Plugin type: minimizer/singlecost

-R, --refiner=

optimizer used for refinement after the main optimizer was called. For supported plug-ins see Plugin type: minimizer/singlecost

-f, --transForm=spline; factory

transformation type. For supported plug-ins see Plugin type: 2dimage/transform

Processing

--threads=-1; int

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).

Example:

Register the image 'moving.png' to the image 'reference.png' by using a rigid transformation model and ssd as cost function. Write the result to output.png

mia-2dimageregistration   -i moving.png -r reference.png -o output.png -f rigid image:cost=ssd

Author(s):

Gert Wollny