GPU Implementation of the Affine Transform for 3D Image Registration

Charles Gillan, Daniel Crookes, Paul Miller, Kevin Boyle

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Citations (Scopus)


Recent developments in 3D low-light level CCD (L3CCD) image capture have resulted in vast volumes of data being produced in real time which require image registration. The amount of data involved means that acceleration of the processing is essential. One of the key steps in one iterative registration algorithm is the application of an affine transform to all the planes of a 3D image. This paper presents details and performance results for a number of parallelized implementations of the affine transform on the NVIDIA 8800 GPU series, and shows that the transform runs 128 times faster on the GPU than a C++ version on a PC, or 54 times faster when data transfer between the GPU and the host PC is included.
Original languageEnglish
Title of host publicationProceedings of 2009 13th International Machine Vision and Image Processing Conference
Place of PublicationPiscataway NJ 08855-1331
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages5
ISBN (Print)978-1-4244-4875-3
Publication statusPublished - 04 Sep 2009


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