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International Conference on Geo-Informatics in Resource Management and Sustainable Ecosystem

2015, GRMSE 2015: Geo-Informatics in Resource Management and Sustainable Ecosystem pp 169–176Cite as

Spaceborne Multispectral Image Compression by Exploiting Temporal Correlation

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 569))

Abstract

Earth observation satellites usually scan the ground at a fixed period to capture remote sensing images. It’s no doubt that there exists a strong correlation between images obtained at a small interval. This paper is devoted to the compression of spaceborne multispectral images and investigating the coding gain obtained by exploiting temporal correlation. To exploit temporal correlation, a temporal compensation (TC) scheme based on rate-distortion optimization (RDO) is proposed to remove redundancies between two adjacent-period multispectral images along temporal direction and a wavelet-based coding method is used to encode residue images. Experimental results indicate that the TC-based method produces significant improvement compared to those coding schemes of only exploiting spectral and spatial correlation.

This work was supported by the Chinese Natural Science Foundation (61201452).

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Authors and Affiliations

  1. School of Mathematic and Computer Science, Wuhan Polytechnic University, Wuhan, 430023, Hubei, China

    Shigao Li & Liming Jia

Authors
  1. Shigao Li
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  2. Liming Jia
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Corresponding author

Correspondence to Shigao Li .

Editor information

Editors and Affiliations

  1. Wuhan University , Wuhan, China

    Fuling Bian

  2. Eastern Michigan University , Ypsilanti, China

    Yichun Xie

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Li, S., Jia, L. (2016). Spaceborne Multispectral Image Compression by Exploiting Temporal Correlation. In: Bian, F., Xie, Y. (eds) Geo-Informatics in Resource Management and Sustainable Ecosystem. GRMSE 2015 2015. Communications in Computer and Information Science, vol 569. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-49155-3_16

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  • DOI: https://doi.org/10.1007/978-3-662-49155-3_16

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-49154-6

  • Online ISBN: 978-3-662-49155-3

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