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Fast Video Stream Super Resolution Reconstruction based on CUDA
LI Ying 1 *,HU Jie 1 #,LI Hailiang 2,SHEN Qiang 3
1.School of Computer Science, Northwestern Polytechnical University, Xi'an, China, 710129
2.Department of Electronic and Information Engineering, the Hong Kong Polytechnic University, Hong Kong, China
3.Department of Computer Science, Aberystwyth University, UK
*Correspondence author
#Submitted by
Subject:
Funding: the UK Royal Academy of Engineering (No.No. 1314RECI025), the Research Fund for the Doctoral Program of Higher Education of China (No.20126102110041), the Research Fund for the Key Project of Technology Research Plan of Ministry of Public Security (No.No. 2014JSYJA018), the Doctorate Foundation of Northwestern Polytechnical University (No.No. CX201414)
Opened online:11 December 2015
Accepted by: none
Citation: LI Ying,HU Jie,LI Hailiang.Fast Video Stream Super Resolution Reconstruction based on CUDA[OL]. [11 December 2015] http://en.paper.edu.cn/en_releasepaper/content/4663992
 
 
This paper presents a parallel GPU-based solution for video stream super resolution reconstruction. We propose an approach, using the computer unified device architecture (CUDA) platform developed by NVIDIA, to partition the steps of the non-local iterative back projection (NLIBP) algorithm (which is designed for single image super resolution reconstruction). The approach also exploits the redundant information of the video stream in the time-space domain in an effort to further reduce the unnecessary searching work in the motion estimation process. The use of CUDA enhances the programmability and flexibility for general-purpose computation of GPU. Experimental results show that, with the assistance of CUDA, the processing time is approximately 8 times faster than that of using CPU only in C++ language, while preserving good visual quality of the reconstructed video stream.
Keywords:technology of computer application; super resolution; non-local similarity; motion estimation; iterative back projction; GPU; CUDA
 
 
 

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