Image stack alignment in full-field X-ray absorption spectroscopy using SIFT_PyOCL
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 im...
| Publié dans: | Journal of synchrotron radiation. - 1994. - 21(2014), Pt 2 vom: 07. März, Seite 456-61 |
|---|---|
| Auteur principal: | |
| Autres auteurs: | , |
| Format: | Article en ligne |
| Langue: | English |
| Publié: |
2014
|
| Accès à la collection: | Journal of synchrotron radiation |
| Sujets: | Journal Article GPU SIFT OpenCL XAS full-field hyperspectral imaging image alignment |
| Résumé: | 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 |
|---|---|
| Description: | Date Completed 20.10.2014 Date Revised 24.02.2014 published: Print-Electronic Citation Status MEDLINE |
| ISSN: | 1600-5775 |
| DOI: | 10.1107/S160057751400023X |