Rigid registration algorithm based on the minimization of the total variation of the difference map

Abstract

Image registration is broadly used in various scenarios in which similar scenes in different images are to be aligned. However, image registration becomes challenging when the contrasts and backgrounds in the images are vastly different. This work proposes using the total variation of the difference map between two images (TVDM) as a dissimilarity metric in rigid registration. A method based on TVDM minimization is implemented for image rigid registration. The method is tested with both synthesized and real experimental data that have various noise and background conditions. The performance of the proposed method is compared with the results of other rigid registration methods. It is demonstrated that the proposed method is highly accurate and robust and outperforms other methods in all of the tests. The new algorithm provides a robust option for image registrations that are critical to many nano-scale X-ray imaging and microscopy applications.

Surface coating by mechanofusion modulates bulk charging pathways and battery performance of Ni-rich layered cathodes

“…XANES-3DTXM on such powders was performed at beamline 18-ID at National Synchrotron Light Source II (NSLS-II), Brookhaven National Laboratory. A scientific package, TXM-Sandbox, was used to reconstruct and align the tomographic datasets ( 42 , 43 ). Ni K-edge white-line energy was extracted to benchmark the relative oxidation state of Ni by fitting the spectra in MATLAB with a combination of trigonometric and second-order polynomial functions for the best convergence.…”