A Parallel Method of Atmospheric Correction for Multispectral High Spatial Resolution Remote Sensing Images

被引：0
|
作者：
Zhao, Shaoshuai [1 ,2 ]
Ni, Chen [3 ]
Cao, Jing [3 ]
Li, Zhengqiang [2 ]
Chen, Xingfeng [2 ]
Ma, Yan [2 ]
Yang, Leiku [1 ]
Hou, Weizhen [2 ]
Qie, Lili [2 ]
Ge, Bangyu [2 ]
Liu, Li [4 ]
Xing, Jin [5 ]
机构：
[1] Henan Polytech Univ, Sch Surveying & Land Informat Engn, Jiaozuo 454003, Peoples R China
[2] Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, State Environm Protect Key Lab Satellite Remote S, Beijing 100101, Peoples R China
[3] China Acad Space Technol, Inst Spacecraft Syst Engn, Beijing 100094, Peoples R China
[4] China Ctr Resources Satellite Data & Applicat, Beijing 100094, Peoples R China
[5] China Natl Space Adm, Earth Observat Program Ctr, Beijing 100101, Peoples R China
来源：
MIPPR 2017: REMOTE SENSING IMAGE PROCESSING, GEOGRAPHIC INFORMATION SYSTEMS, AND OTHER APPLICATIONS | 2018年 / 10611卷
基金：
中国国家自然科学基金;
关键词：
Parallel Computing; Atmospheric Correction; Remote Sensing; Multispectral Image; High Spatial Resolution;
D O I：
10.1117/12.2283380
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The remote sensing image is usually polluted by atmosphere components especially like aerosol particles. For the quantitative remote sensing applications, the radiative transfer model based atmospheric correction is used to get the reflectance with decoupling the atmosphere and surface by consuming a long computational time. The parallel computing is a solution method for the temporal acceleration. The parallel strategy which uses multi-CPU to work simultaneously is designed to do atmospheric correction for a multispectral remote sensing image. The parallel framework's flow and the main parallel body of atmospheric correction are described. Then, the multispectral remote sensing image of the Chinese Gaofen-2 satellite is used to test the acceleration efficiency. When the CPU number is increasing from 1 to 8, the computational speed is also increasing. The biggest acceleration rate is 6.5. Under the 8 CPU working mode, the whole image atmospheric correction costs 4 minutes.
引用
收藏
页数：5
相关论文
共 50 条
  • [41] DIFET: DISTRIBUTED FEATURE EXTRACTION TOOL FOR HIGH SPATIAL RESOLUTION REMOTE SENSING IMAGES
    Eken, S.
    Aydin, E.
    Sayar, A.
    4TH INTERNATIONAL GEOADVANCES WORKSHOP - GEOADVANCES 2017: ISPRS WORKSHOP ON MULTI-DIMENSIONAL & MULTI-SCALE SPATIAL DATA MODELING, 2017, 4-4 (W4): : 209 - 213
  • [42] Study on Rocky Coastline Extraction of High-Spatial-Resolution Remote Sensing Images
    Wang, Liyan
    Hou, Chen
    Li, Peng
    Qu, Hui
    Zhang, Jie
    PROCEEDINGS OF THE 2016 INTERNATIONAL CONFERENCE ON COMPUTER AND INFORMATION TECHNOLOGY APPLICATIONS (ICCITA), 2016, 53 : 150 - 153
  • [43] Evaluation of Port Prosperity Based on High Spatial Resolution Satellite Remote Sensing Images
    Suo Anning
    Xu Jingping
    Li Xuchun
    Wei Baoquan
    CHINESE GEOGRAPHICAL SCIENCE, 2020, 30 (05) : 889 - 899
  • [44] Multi-granularity synthesis segmentation for high spatial resolution Remote sensing images
    Yi, Lina
    Liu, Pengfei
    Qiao, Xiaojun
    Zhang, Xiaoning
    Gao, Yuan
    Feng, Boyan
    35TH INTERNATIONAL SYMPOSIUM ON REMOTE SENSING OF ENVIRONMENT (ISRSE35), 2014, 17
  • [45] An explicit fuzzy supervised classification method for multispectral remote sensing images
    Melgani, F
    Al Hashemy, BAR
    Taha, SMR
    IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2000, 38 (01): : 287 - 295
  • [46] HIGH-RESOLUTION RADAR FOR REMOTE ATMOSPHERIC SENSING
    RICHTER, JH
    IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS, 1975, 11 (03) : 423 - 423
  • [47] Spatial Electric Load Forecasting Method Based on High-Level Encoding of High-Resolution Remote Sensing Images
    Wang, Bowen
    Sun, Hongbin
    FRONTIERS IN ENERGY RESEARCH, 2022, 10
  • [48] Remote sensing of aerosols in urban areas from very high spatial resolution images: application of the OSIS code to multispectral PELICAN airborne data
    Thomas, Colin
    Briottet, Xavier
    Santer, Richard
    INTERNATIONAL JOURNAL OF REMOTE SENSING, 2013, 34 (03) : 919 - 937
  • [49] Suppression of vegetation in multispectral remote sensing images
    Yu, Le
    Porwal, Alok
    Holden, Eun-Jung
    Dentith, Michael Charles
    INTERNATIONAL JOURNAL OF REMOTE SENSING, 2011, 32 (22) : 7343 - 7357
  • [50] Secure distribution for high resolution remote sensing images
    Liu, Jin
    Sun, Jing
    Xu, Zheng Q.
    JOURNAL OF APPLIED REMOTE SENSING, 2010, 4
12345