2D image similarity kernels evaluate the according similarity measure between two images by using a mask. 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.
local normalized cross correlation with masking support.. Supported parameters are:
Name | Type | Default | Description |
---|---|---|---|
w | uint in [1, 256] | 5 | half width of the window used for evaluating the localized cross correlation |
Spline parzen based mutual information with masking.. Supported parameters are:
Name | Type | Default | Description |
---|---|---|---|
cut | float in [0, 40] | 0 | Percentage of pixels to cut at high and low intensities to remove outliers |
mbins | uint in [1, 256] | 64 | Number of histogram bins used for the moving image |
mkernel | factory | [bspline:d=3] | Spline kernel for moving image parzen hinstogram. For supported plug-ins see Plugin type: 1d/splinekernel |
rbins | uint in [1, 256] | 64 | Number of histogram bins used for the reference image |
rkernel | factory | [bspline:d=0] | Spline kernel for reference image parzen hinstogram. For supported plug-ins see Plugin type: 1d/splinekernel |
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 maskedimage:2dimage/fullcost