{"title":"A comparison of sequential and GPU-accelerated implementations of B-spline signal processing operations for 2-D and 3-D images","authors":"A. Karantza, Sonia Lopez-Alarcon, N. Cahill","doi":"10.1109/IPTA.2012.6469565","DOIUrl":null,"url":null,"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.","PeriodicalId":267290,"journal":{"name":"2012 3rd International Conference on Image Processing Theory, Tools and Applications (IPTA)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 3rd International Conference on Image Processing Theory, Tools and Applications (IPTA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IPTA.2012.6469565","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
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.
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