A comparison of sequential and GPU-accelerated implementations of B-spline signal processing operations for 2-D and 3-D images

Author

Karantza, A. ; Alarcon, S.L. ; Cahill, Nathan D.

Author_Institution

Dept. of Comput. Eng., Rochester Inst. of Technol., Rochester, NY, USA

fYear

2012

fDate

15-18 Oct. 2012

Firstpage

74

Lastpage

79

Abstract

B-spline signal processing operations are widely used in the analysis of two and three-dimensional images. In this paper, we investigate and compare some of these basic operations (direct transformations, indirect transformations, and computation of partial derivatives) by (1) recursive filter based implementations in MATLAB and C++, and (2) GPU-accelerated implementations in CUDA. All operations are compared at a variety of resolution levels on a 2-D panoramic image as well as a 3-D magnetic resonance (MR) image. Results indicate significant improvements in efficiency for the CUDA implementations. A MATLAB toolkit implementing the various B-spline signal processing tasks as well as the C++ and CUDA implementation described here is currently publicly available.

Keywords

C++ language; graphics processing units; image resolution; parallel architectures; recursive filters; splines (mathematics); 2D image; 2D panoramic image; 3D image; 3D magnetic resonance; B-spline signal processing; C++; CUDA; GPU-accelerated implementation; MATLAB; indirect transformation; partial derivative; recursive filter; resolution level; Convolution; Graphics processing units; Kernel; Laplace equations; MATLAB; Splines (mathematics); Transforms; B-spline; GPU; filtering; interpolation;

fLanguage

English

Publisher

ieee

Conference_Titel

Image Processing Theory, Tools and Applications (IPTA), 2012 3rd International Conference on

Conference_Location

Istanbul

ISSN

2154-5111

Print_ISBN

978-1-4673-2585-1

Type

conf

DOI

10.1109/IPTA.2012.6469565

Filename

6469565