Title :
A GPU Accelerated Algorithm for Compressive Sensing Based Image Super-Resolution
Author :
Wu, Xifei ; Xiang, Hui ; Lu, Peng
Author_Institution :
Sch. of Comput. Sci. & Technol., Shandong Univ., Jinan, China
Abstract :
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.
Keywords :
coprocessors; image reconstruction; image resolution; signal representation; ATI Stream platform; GPU accelerated algorithm; compressive sensing; image reconstruction; image super-resolution; parallel algorithm; serial program; Acceleration; Compressed sensing; Graphics processing unit; Image reconstruction; Image resolution; Kernel; Signal resolution; Compressive Sensing; GPU; Image Super-resolution; parallel computing;
Conference_Titel :
Digital Media and Digital Content Management (DMDCM), 2011 Workshop on
Conference_Location :
Hangzhou
Print_ISBN :
978-1-4577-0271-6
Electronic_ISBN :
978-0-7695-4413-7
DOI :
10.1109/DMDCM.2011.10
