Plugin type: 2dimage/cost

2D image similarity kernels evaluate the according similarity measure between two images. These kernels may be used standalone, like e.g. in linear registration, or will be called from generalized image similarity cost plug-ins that also take care of transforming and scaling the images during the image registration process.

Plugins:

lncc lsd mi ncc ngf ssd ssd-automask

lncc

local normalized cross correlation with masking support.. Supported parameters are:

NameTypeDefaultDescription
wuint in [1, 256]5half width of the window used for evaluating the localized cross correlation

lsd

Least-Squares Distance measure. (This plug-in doesn't take parameters)

mi

Spline parzen based mutual information.. Supported parameters are:

NameTypeDefaultDescription
cutfloat in [0, 40]0Percentage of pixels to cut at high and low intensities to remove outliers
mbinsuint in [1, 256]64Number of histogram bins used for the moving image
mkernelfactory[bspline:d=3]Spline kernel for moving image parzen hinstogram. For supported plug-ins see Plugin type: 1d/splinekernel
rbinsuint in [1, 256]64Number of histogram bins used for the reference image
rkernelfactory[bspline:d=0]Spline kernel for reference image parzen hinstogram. For supported plug-ins see Plugin type: 1d/splinekernel

ncc

normalized cross correlation.. (This plug-in doesn't take parameters)

ngf

This function evaluates the image similarity based on normalized gradient fields. Various evaluation kernels are availabe.. Supported parameters are:

NameTypeDefaultDescription
evaldictds
plugin subtype
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:

NameTypeDefaultDescription
autothreshfloat in [0, 1000]0Use automatic masking of the moving image by only takeing intensity values into accound that are larger than the given threshold
normbool0Set 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:

NameTypeDefaultDescription
rthreshdouble0Threshold intensity value for reference image
sthreshdouble0Threshold intensity value for source image

Plugin consumers:

mia-2dcost mia-2dimageregistration mia-2dmany2one-nonrigid mia-2dmulti-force mia-2dmultiimageregistration mia-2dmyoica-full mia-2dmyoica-nonrigid mia-2dmyoica-nonrigid-parallel mia-2dmyoicapgt mia-2dmyoperiodic-nonrigid mia-2dmyoserial-nonrigid mia-2dmyoset-all2one-nonrigid image:2dimage/fullcost