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Proceedings Paper

Secret spatial information hiding technique for remote sensing image
Author(s): Xianmin Wang; Cheng Wang; Jianzhong Zhou; Yongchuan Zhang
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Paper Abstract

In this paper, we introduced information hiding technique into remote sensing area, proposed its characters, requirements and difference from general information hiding technique and illuminated that general image hiding algorithm doesn't adapt to remote sensing image. There often exists some secret annotation related to a remote sensing image, therefore we proposed a new secret spatial information hiding technique for remote sensing image, which realizes to hide the secret spatial annotation into the related remote sensing image. And we also proposed a wavelet information hiding algorithm adapting to features of a remote sensing image based on DWT embedding strategy and HVS character. The experimental results show that the secret spatial information hiding technique and algorithm for a remote sensing image proposed in the paper not only has the advantages of good transparency, strongness, large information capacity and correct extraction of secret, but also has a strong robustness against JPEG lossy compression and noise adding. Furthermore the novel spatial information hiding technique and algorithm has no influence on applied value of a remote sensing image and doesn't need the original remote sensing image while extracting the secret spatial information, namely it is a blind algorithm.

Paper Details

Date Published: 5 March 2008
PDF: 13 pages
Proc. SPIE 6623, International Symposium on Photoelectronic Detection and Imaging 2007: Image Processing, 66230G (5 March 2008); doi: 10.1117/12.791280
Show Author Affiliations
Xianmin Wang, China Univ. of Geosciences (China)
Cheng Wang, Huazhong Univ. of Science and Technology (China)
Jianzhong Zhou, Huazhong Univ. of Science and Technology (China)
Yongchuan Zhang, Huazhong Univ. of Science and Technology (China)


Published in SPIE Proceedings Vol. 6623:
International Symposium on Photoelectronic Detection and Imaging 2007: Image Processing

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