Indexed by:会议论文
Date of Publication:2012-09-30
Included Journals:EI、CPCI-S、Scopus
Page Number:849-852
Key Words:super-resolution; GPU computing; CUDA
Abstract:Super-resolution reconstruction (SRR) proposes a fusion of several low-quality images into one higher quality result with better optical resolution. However, due to the vast amount of calculation of the SRR algorithm, its implementation is too slow. In this paper, we present a GPU-based parallel implementation on SRR algorithm. The compute unified device architecture (CUDA) is a programming approach for performing scientific calculations on a graphics processing unit (GPU) as a data-parallel computing device. The proposed GPU-based implementation using CUDA is up to approximately 200 times faster than the corresponding optimized CPU counterparts.
Professor
Supervisor of Doctorate Candidates
Supervisor of Master's Candidates
Gender:Female
Alma Mater:大连理工大学
Degree:Doctoral Degree
School/Department:信息与通信工程学院
Business Address:海山楼A420
Contact Information:lslwf@dlut.edu.cn
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