
Proceedings Paper
A CPU/GPU collaborative approach to high-speed remote sensing image rectification based on RFMFormat | Member Price | Non-Member Price |
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Paper Abstract
Image rectification is a common task in remote sensing application and usually time-consuming for large-size images.
Based on the characteristics of the Rational Functional Model (RFM)-based rectification process, this paper proposes a
novel CPU/GPU collaborative approach to high-speed rectification of remote sensing images. Three performance
optimization strategies are presented in detail, including maximizing device occupancy, improving memory access
efficiency and increasing instruction throughput. Experimental results using SPOT-5 and ZiYuan-3 (ZY3) remote
sensing images show that the proposed method can achieve the processing speed up to 8GB/min, which significantly
exceeds that of common commercial software. Real-time remote sensing image rectification can be expected with further
optimized algorithm and more efficient I/O operation.
Paper Details
Date Published: 14 May 2014
PDF: 8 pages
Proc. SPIE 9158, Remote Sensing of the Environment: 18th National Symposium on Remote Sensing of China, 91580F (14 May 2014); doi: 10.1117/12.2063894
Published in SPIE Proceedings Vol. 9158:
Remote Sensing of the Environment: 18th National Symposium on Remote Sensing of China
Qingxi Tong; Jie Shan; Boqin Zhu, Editor(s)
PDF: 8 pages
Proc. SPIE 9158, Remote Sensing of the Environment: 18th National Symposium on Remote Sensing of China, 91580F (14 May 2014); doi: 10.1117/12.2063894
Show Author Affiliations
Yiwei Sun, Institute of Remote Sensing Applications (China)
Bin Liu, Institute of Remote Sensing Applications (China)
Xiliang Sun, Institute of Remote Sensing Applications (China)
Bin Liu, Institute of Remote Sensing Applications (China)
Xiliang Sun, Institute of Remote Sensing Applications (China)
Wenhui Wan, Institute of Remote Sensing Applications (China)
Kaichang Di, Institute of Remote Sensing Applications (China)
Zhaoqin Liu, Institute of Remote Sensing Applications (China)
Kaichang Di, Institute of Remote Sensing Applications (China)
Zhaoqin Liu, Institute of Remote Sensing Applications (China)
Published in SPIE Proceedings Vol. 9158:
Remote Sensing of the Environment: 18th National Symposium on Remote Sensing of China
Qingxi Tong; Jie Shan; Boqin Zhu, Editor(s)
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