Woolz Image Processing  Version 1.7.0
WlzRegisterCCor - registers a pair of 2D domain objects with grey values using frequency domain cross-correlation.
WlzRegisterCCor [-h] [-v] [-o<out obj>] [-i <init tr>] [-n]
                [-r] [-t] [-w <win fn>] [-R #] [-T #,#] [-V]
                [<in obj 0>] [<in obj 1>]
-h Help, prints usage message.
-o Output file name for affine transform.
-i Initial affine transform object.
-n Use Gaussian noise (may be useful inplace of a window function).
-r Find the rigid body (aka registration) transform, default.
-t Find the translation only transform.
-w Window function name, this must be one of: blackman, hamming, hanning, none, parzen, rectangle or welch.
-R Maximum rotation.
-T Maximum translation.
-V Invert grey values. Objects must have the background with low and the foreground with high values.
Attempts to register two objects using an frequency domain cross-correlation algorithm. The two objects must be 2D spatial domain objects with grey values. It is important to give sensible maximum translation and rotation values. If they are to small the itteration probably will not converge to the true maximum cross-correlation values, but if the values are too large the algorithm will take both more time and memory. The input objects are read from stdin and values are written to stdout unless the filenames are given.
WlzRegisterCCor -w hamming -o out-tr.wlz -R 10 -T 20,30 -r in0.wlz in1.wlz
A rigid body affine transform is found by registering in1.wlz to in0.wlz using a cross-correlation based registration algorithm, with a Hamming window function being used to reduce the effect of the source and target image boundaries. The affine transform is then written to out-tr.wlz. The maximum rotation in a single itteration is 10 degrees and the maximum translation in a single itteration is 20 columns and 30 rows.
See Also
WlzIntro(1) WlzRegisterICP(1) WlzRegCCorObjs(3)