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An Invalid Cloud Region Masking Method for Remote Sensing Image Compression

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Abstract

An invalid cloud region masking method based on local edge context is proposed for the compression of remote sensing images. Through analyzing the characteristics of various compression algorithms and taking the local edge information of the cloud region into account, the decompression quality is improved. First, according to the cloud mask information, labeling the connected cloud region, second, performing region growth on the labeled mask image, then differing the two mask images to obtain the local edge context, and finally different invalid cloud regions are filled with the average of the respective local edge context pixels. Using the image testing set generated from QuickBird and OrbView images, our method’s impact on six common remote sensing image compression algorithms is analyzed experimentally. The experimental results show that our masking method can improve the decompressed image quality when the compression ratio is certain. When the image quality is fixed, it can further reduce the compressed bitrate. For onboard application, our masking method can increase the onboard imaging time of the satellites, and eventually improve the onboard specifications of remote sensing satellites.

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ACKNOWLEDGMENTS

Thanks are due to Professor C. Bian for assistance with the experiments and to Q. Hou for valuable discussion.

Funding

This work was supported by National Natural Science Foundation of China (grant no. 61305107), Fundamental Research Funds for the Central Universities (grant no. 3122014C017) and Scientific Research Foundation of CAUC (grant no. 2013QD17X).

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Authors and Affiliations

  1. Department of Computer, Civil Aviation University of China, Dongli District Tianjin, 300300, Tianjin, China

    Huaichao Wang & Jing Wang

  2. National Space Science Center, Chinese Academy of Sciences, Haidian District, 100190, Beijing, China

    Hai Zhou

Authors
  1. Huaichao Wang
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  2. Hai Zhou
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  3. Jing Wang
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Corresponding authors

Correspondence to Huaichao Wang, Hai Zhou or Jing Wang.

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We declare that we do not have any commercial or associative interest that represents a conflict of interest in connection with the work submitted.

Additional information

Huaichao Wang was born in Tianjin, China in 1984. He received his PhD degrees in Computer Science from National Space Science Center, Chinese Academy of Sciences in 2011. He has been a lecture of Department of Computer Science and Technology, Civil Aviation University of China since 2013. His research interests include on-board information processing and machine learning.

Jing Wang was born in Shanxin, China in 1980. She received her PhD degrees in Computer Science from Harbin Engineering University in 2008. She has been a lecture of Department of Computer Science and Technology, Civil Aviation University of China since 2008. Her research interests include information processing and machine learning.

Hai Zhou was born in Anhui, China in 1987. He received his M.Sc. degrees in Xidian University in 2010. He has been a associate professor of National Space Science Center, Chinese Academy of Sciences since 2010. His research interests include on–board image processing and machine learning.

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Wang, H., Zhou, H. & Wang, J. An Invalid Cloud Region Masking Method for Remote Sensing Image Compression. Pattern Recognit. Image Anal. 30, 134–144 (2020). https://doi.org/10.1134/S1054661820010162

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