GPU Implementation of the Affine Transform for 3D Image Registration

被引：4

作者：

Crookes, Danny ^{[1
]}

Boyle, Kevin ^{[1
]}

Miller, Paul ^{[1
]}

Gillan, Charles ^{[1
]}

机构：

[1] Queens Univ Belfast, Inst Elect Commun & Informat Technol, Belfast BT3 9DT, Antrim, North Ireland

来源：

2009 13TH INTERNATIONAL MACHINE VISION AND IMAGE PROCESSING CONFERENCE | 2009年

关键词：

D O I：

10.1109/IMVIP.2009.34

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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

引用

页码：151 / 155

页数：5

共 5 条

[1]

Gonzalez R.C., 2008, Digital Image Processing, V3rd

[2]

GRIBBEN H, 2007, P BMVC 2007 WARW

[3] Accelerating molecular modeling applications with graphics processors [J].