Title :
Parallel fast Global K-Means algorithm for synthetic aperture radar image change detection using OpenCL
Author :
Huming Zhu;Qingyu Zhang;Xinying Ren;Licheng Jiao
Author_Institution :
Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China, Xidian University, Xi´an, China
fDate :
7/1/2015 12:00:00 AM
Abstract :
In this article, Fast Global K-Means (FGKM) for Synthetic Aperture Radar (SAR) image change detection is presented. On account of the time-consuming of FGKM algorithm and the real-time demand, we present a Parallel Fast Global K-Means (P-FGKM) algorithm. We parallelize the selection of initial cluster centers which is the most time-consuming step of FGKM algorithm. The proposed algorithm is implemented based on Open Computing Language (OpenCL). The experiments are carried out on a variety of heterogeneous computing devices, such as Multi-core CPU, GPU, Intel HD Graphics, Many Integrated Core (MIC). Experiment results show that the proposed algorithm can achieve a good speedup up to 86 times on such devices.
Keywords :
"Clustering algorithms","Change detection algorithms","Graphics processing units","Synthetic aperture radar","High definition video","Kernel","Algorithm design and analysis"
Conference_Titel :
Geoscience and Remote Sensing Symposium (IGARSS), 2015 IEEE International
Electronic_ISBN :
2153-7003
DOI :
10.1109/IGARSS.2015.7325765