A GPU Accelerated Algorithm for Compressive Sensing Based Image Super-Resolution
Sch. of Comput. Sci. & Technol., Shandong Univ., Jinan, China
Workshop on Digital Media and Digital Content Management (DMDCM), 2011
@inproceedings{wu2011gpu,
title={A GPU Accelerated Algorithm for Compressive Sensing Based Image Super-Resolution},
author={Wu, X. and Xiang, H. and Lu, P.},
booktitle={2011 Workshop on Digital Media and Digital Content Management},
pages={198–202},
year={2011},
organization={IEEE}
}
This paper presents a parallel algorithm designed for Super-resolution Image Reconstruction based on Compressive sensing in the ATI Stream platform. In the accelerating process, we select part of the serial program as the objects to be sped up according to the execution time of each stage, set appropriate parallel granularity to make full use of GPU’s computational horsepower, and make a rational use of different kinds of memory space in GPU. At last, the result of the parallel algorithm is shown and analyzed. Compared to the serial algorithm, parallel algorithm has significantly accelerated results.
September 2, 2011 by hgpu
