Volume 41 Issue 1
Jan.  2016
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LIU Po, GONG Jianhua. Parallel Construction of Global Pyramid for Large Remote Sensing Images[J]. Geomatics and Information Science of Wuhan University, 2016, 41(1): 117-122. DOI: 10.13203/j.whugis20130718
Citation: LIU Po, GONG Jianhua. Parallel Construction of Global Pyramid for Large Remote Sensing Images[J]. Geomatics and Information Science of Wuhan University, 2016, 41(1): 117-122. DOI: 10.13203/j.whugis20130718
shu

Parallel Construction of Global Pyramid for Large Remote Sensing Images

  • 1.

    Chinese Academy of Surveying and Mapping, Beijing 100830, China;

  • 2.

    State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China

Funds: The Key Knowledge Innovative Project of the Chinese Academy of Sciences, No. KZCX2-EW-318; the National Key Technology R&D Program of China, No. 2014ZX10003002; the National Natural Science Foundation of China, No. 41371387.
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  • Received Date: September 10, 2014
  • Published Date: January 04, 2016
    Graphical Abstract
    • Abstract
  • The pyramid model is the basis for visualization and processing of massive remote sensing data in a virtual globe system. It produces large amounts of data tiles in the process of building pyramids however, and the traditional serial CPU algorithm has difficulties satisfying requests for large images. This paper proposes a parallel global pyramid approach that exploits GPU capabilities and multi-threading to enable memory-intensive and computation-intensive tasks. A two-level decomposition strategy was developed to migrate the performance bottlenecks in data transfers among the GPU, CPU, and disk. A multi-threading strategy was used to reduce the delay between CPU and disk, and pin-memory for GPU global delay. Finally, the GPU is used to complete large-scale parallel resample computing and constructing an octree structure used to maximize reuse of data in the graphic memory. Experimental results show that the proposed method can significantly improve pyramid construction speed for large remote sensing images.
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    • References (18)
  • [1]
    Goodchild M F, Guo H, Annoni A, et al. Next-Generation Digital Earth[J]. The National Academy of Sciences, 2012, 109(28):11 088-11 094
    [2]
    Brovelli M A, Zamboni G. Virtual Globes for 4D Environmental Analysis[J]. Applied Geomatics, 2012, 4(3):163-172
    [3]
    Turk F J, Hawkins J, Richardson K, et al. A Tropical Cyclone Application for Virtual Globes[J]. Computers & Geosciences, 2011, 37(1):13-24
    [4]
    Chien N Q, Keat T S. Google Earth as a Tool in 2-D Hydrodynamic Modeling[J]. Computers & Geosciences, 2011, 37(1):38-46
    [5]
    Tooth S. Virtual Globes:a Catalyst for the Re-enchantment of Geomorphology?[J]. Earth Surface Processes and Landforms, 2006, 31(9):1 192-1 194
    [6]
    Deng X. Research on Service Architecture and Algorithms for Grid spatial Data[J]. Acta Geodaetica et Cartographica Sinaca, 2003, 36(4):362-367(邓雪清. 栅格型空间数据服务体系结构与算法研究[J]. 测绘学报,2003, 36(4):362-367)
    [7]
    Viola I, Kanitsar A, Groller M E. Hardware-Based Nonlinear Filtering and Segmentation Using High-Level Shading Languages[M]. New York:IEEE Computer Society, 2003
    [8]
    Xie J, Yang C, Zhou B, et al. High-Performance Computing for the Simulation of Dust Storms[J]. Computers, Environment and Urban Systems, 2010, 34(4):278-290
    [9]
    Walsh S D, Saar M O, Bailey P, et al. Accelerating Geoscience and Engineering System Simulations on Graphics Hardware[J]. Computers & Geosciences, 2009, 35(12):2 353-2 364
    [10]
    Zhang Y, Liu P, Yang M. Accelerating Bipartite Graph Co-Clustering Based on GPU[J]. Geography and Geo-Information Science, 2013, 29(4):99-103(张宇,刘坡,杨敏华.基于GPU的二部图联合聚类并行算法研究[J].地理与地理信息科学,2013, 29(4):99-103)
    [11]
    Zhang J, You S. CudaGIS:Report on the Design and Realization of a Massive Data Parallel GIS on GPUs[C]. The Third ACM SIGSPATIAL International Workshop on GeoStreaming, Redondo Beach, California, USA,2012
    [12]
    Zhang B, Yang W, Gao L, et al. Real-Time Target Detection in Hyperspectral Images Based on Spatial-Spectral Information Extraction[J]. Eurasip Journal on Advances in Signal Processing, 2012, 2012(1):1-15
    [13]
    Steinbach M, Hemmerling R. Accelerating Batch Processing of Spatial Raster Analysis Using GPU[J]. Computers & Geosciences, 2012, 45:212-220
    [14]
    Giannesini F, Le Saux B. GPU-accelerated One-Class SVM for Exploration of Remote Sensing Data[C]. 2012 IEEE International Geoscience and Remote Sensing Symposium, Munich, Germany,2012
    [15]
    Yang C, Wu H, Huang Q, et al. Using Spatial Principles to Optimize Distributed Computing for Enabling the Physical Science Discoveries[J]. The National Academy of Sciences, 2011, 108(14):5 498-5 503
    [16]
    Xiao H, Zhou Q, Zhang Z. Parallel Algorithm of Harris Corner Detection Based on Multi-GPU[J]. Geomatics and Information Science of Wuhan University, 2012, 37(7):876-881 (肖汉, 周清雷, 张祖勋. 基于多GPU的Harris角点检测并行算法[J].武汉大学学报·信息科学版,2012, 37 (7):876-881)
    [17]
    Kang J, Du Z, Liu R. Parallel Image Resample Algorithm Based on GPU for Land Remote Sensing Data Management[J]. Journal of Zhejiang University(Science Edition), 2011, 38(6):695-700(康俊锋, 杜震洪, 刘仁义, et al. 基于GPU加速的遥感影像金字塔创建算法及其在土地遥感影像管理中的应用[J]. 浙江大学学报(理学版), 2011, 38(6):695-700)
    [18]
    Parker J A, Kenyon R V, Troxel D E. Comparison of Interpolating Methods for Image Resampling[J]. IEEE Transactions on Knowledge and Data Engineering, 1983, 2(1):31-39
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