
Proceedings Paper
A fast preprocessing algorithm for massive MODIS 1B dataFormat | Member Price | Non-Member Price |
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Paper Abstract
MODIS 1B data preprocessing consists of "bowtie" effect elimination and geometric correction. The paper proposes a
fast preprocessing algorithm. First, partition the input image into small sub-images without "bowtie" effect. Secondly, do
geometric correction to each sub-image. Finally, mosaic each sub-image in the output coordinate system and eliminate
the "bowtie" effect in the process. The proposed algorithm shows both a better geometric performance and faster preprocessing speed. For the massive MODIS 1B data preprocessing, a parallel preprocessing method based on this algorithm above is further proposed. Analysis shows that real-time preprocessing for massive MODIS 1B data can be realized by the parallel algorithm.
Paper Details
Date Published: 8 August 2007
PDF: 10 pages
Proc. SPIE 6752, Geoinformatics 2007: Remotely Sensed Data and Information, 67520X (8 August 2007); doi: 10.1117/12.760468
Published in SPIE Proceedings Vol. 6752:
Geoinformatics 2007: Remotely Sensed Data and Information
Weimin Ju; Shuhe Zhao, Editor(s)
PDF: 10 pages
Proc. SPIE 6752, Geoinformatics 2007: Remotely Sensed Data and Information, 67520X (8 August 2007); doi: 10.1117/12.760468
Show Author Affiliations
Yuanming Shu, Nanjing Univ. (China)
Yongxue Liu, Nanjing Univ. (China)
Zhengyu Duan, Nanjing Univ. (China)
Yongxue Liu, Nanjing Univ. (China)
Zhengyu Duan, Nanjing Univ. (China)
Yu Zhang, Nanjing Univ. (China)
Zhenjie Chen, Nanjing Univ. (China)
Zhenjie Chen, Nanjing Univ. (China)
Published in SPIE Proceedings Vol. 6752:
Geoinformatics 2007: Remotely Sensed Data and Information
Weimin Ju; Shuhe Zhao, Editor(s)
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