xcfShift edit page

measure how far each part of one image moved relative to another

Divides the region the two images share into a grid of tiles and phase correlates each tile against the matching tile of the other image. The result is a displacement per tile, to sub pixel accuracy, and the height of the correlation peak that produced it.

The peak height is not a diagnostic - it is the weight. A tile that landed on featureless background correlates weakly and must not get an equal vote when a transform is fitted through the displacements:

[u,peak,pos] = xcfShift(A,B);
T = spatialTransformShift.fit(pos, pos + u, 'weights', peak);

Description

Only the region where both images are finite is tiled, so the padding an earlier resampling left behind is excluded rather than correlated against. A tile that still contains a non finite value, or that is flat, comes back with NaN in all three outputs - drop those before fitting, which every spatialTransform fit does for you.

Syntax

[u,peak,pos] = xcfShift(A,B)
[u,peak,pos] = xcfShift(mgA,mgB)
[u,peak,pos] = xcfShift(A,B,'ROISize',64,'numROI',[24 18])

Input

`A, B`	`r × c images, the same size`
`mgA, mgB`	`mapImage on the same grid, in which case u and pos are in specimen units rather than pixels`

Output

`u`	`n × 1 vector3d, the displacement from A to B at each tile: the feature at pos in A is at pos + u in B`
`peak`	`n × 1 correlation peak height, the fit weight`
`pos`	`n × 1 vector3d, the tile centres, in A`

Options

`ROISize`	`tile width in pixels, default 2^ceil(log2(rows/4))`
`numROI`	`tiles across, scalar or [nx ny]. A scalar is scaled by the aspect ratio to give ny. Default 24`
`XCFMesh`	`peak upsampling, default 250`
`coarseMesh`	`resolution of the first refinement pass, default 48`

Flags

dedupeBand drop the duplicated band pass indices, see xcfCorrelate

References

M. Guizar-Sicairos, S. T. Thurman, J. R. Fienup, Efficient subpixel image registration algorithms, Optics Letters (2008), Vol. 33, 156.

Citing this page. This page is part of the documentation of MTEX, a free and open source MATLAB toolbox for analyzing and modeling crystallographic textures. It was written by The MTEX Developers and is published at https://mtex-toolbox.github.io/xcfShift.html. If you use MTEX, or reuse text or figures from this page, in your research, please cite

F. Bachmann, R. Hielscher, H. Schaeben: Texture Analysis with MTEX - Free and Open Source Software Toolbox, Solid State Phenomena 160 (2010), 63-68. 10.4028/www.scientific.net/SSP.160.63

BibTeX

@article{bachmann2010mtex,
  author  = {F. Bachmann and R. Hielscher and H. Schaeben},
  title   = {Texture Analysis with MTEX - Free and Open Source Software Toolbox},
  journal = {Solid State Phenomena},
  volume  = {160},
  pages   = {63-68},
  year    = {2010},
  doi     = {10.4028/www.scientific.net/SSP.160.63},
  url     = {https://doi.org/10.4028/www.scientific.net/SSP.160.63}
}

Other papers describing specific MTEX methods are listed under Publications — please cite the one that best fits your application. The MTEX source code is licensed under the GNU General Public License v2.0; the text and figures of this documentation are licensed under CC BY 4.0, which permits reuse — including by automated systems — provided The MTEX Developers and this page are credited.

xcfShift