title: Image stack alignment in full-field X-ray absorption spectroscopy using SIFT_PyOCL.
abstract: Full-field X-ray absorption spectroscopy experiments allow the acquisition of millions of spectra within minutes. However, the construction of the hyperspectral image requires an image alignment procedure with sub-pixel precision. While the image correlation algorithm has originally been used for image re-alignment using translations, the Scale Invariant Feature Transform (SIFT) algorithm (which is by design robust versus rotation, illumination change, translation and scaling) presents an additional advantage: the alignment can be limited to a region of interest of any arbitrary shape. In this context, a Python module, named SIFT_PyOCL, has been developed. It implements a parallel version of the SIFT algorithm in OpenCL, providing high-speed image registration and alignment both on processors and graphics cards. The performance of the algorithm allows online processing of large datasets.
authors.affiliation: European Synchrotron Radiation Facility, Grenoble, France.
authors.forename: Pierre
authors.initials: P
authors.lastname: Paleo
authors.affiliation: European Synchrotron Radiation Facility, Grenoble, France.
authors.forename: Emeline
authors.initials: E
authors.lastname: Pouyet
authors.affiliation: European Synchrotron Radiation Facility, Grenoble, France.
authors.forename: Jérôme
authors.initials: J
authors.lastname: Kieffer
mesh_terms: D000465:Algorithms; D003952:Diagnostic Imaging / Q000379:methods; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional; D012984:Software; D056928:X-Ray Absorption Spectroscopy / Q000379:methods*
keywords: GPU; SIFT OpenCL; XAS; full-field; hyperspectral imaging; image alignment