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Applications of Wavelet Penalty Function in De-Noising for Hyperspectral Images

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Abstract:

With the development of the hyperspectral remote sensing technology, the level of quantitative remote sensing has risen greatly, but varying degrees of random noise is contained. To optimize the use of the remote sensing images and to improve the effectiveness and accuracy of discriminating ground objects according to spectral absorption features, random noise removing is necessary. Aimed at the distribution characteristics of the random point noise of HJ_1A HSI data level 2 product, eliminate the Gaussian white noise by soft-thresholding filtering based on the Birge-Massart penalty function in wavelet domain. And the result shows that the method can not only remove the additive noise effectively, but also retain most of the feature information and edge details of the original image. Therefore, the method could provide necessary support for quantitative use of HJ_1A HSI data.

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Periodical:

Applied Mechanics and Materials (Volumes 263-266)

Pages:

2498-2501

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.263-266.2498

Citation:

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Online since:

December 2012

Authors:

Ji Ning Yan*, Ke Fa Zhou, Li Sun, Yan Fang Qin, Shu Guang Zhou, Nan Xiang

Keywords:

Gaussian White Noise, Hyper-Spectral, Penalty Function, Soft Threshold, Wavelet Domain

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© 2013 Trans Tech Publications Ltd. All Rights Reserved

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References

[1] J. Chen, H. Lin and Y. Shao: International Journal of Remote Sensing. 27(2006)1717-1723.

Google Scholar

[2] Xiaofang Guo, Runsheng Wang: Journal of remote sensing. 3(1999)183-186.

Google Scholar

[3] Guangming Shi, Xiaotian Wang and Li Zhang: J. Infrared Millim. Waves. 27(2008) 214-218.

Google Scholar

[4] Yangyang Zhang. Shandong Normal University, 2011. (In Chinese)

Google Scholar

[5] B.K.P. Horn, R.J. Woodham: Computer Graphics and Image Processing. 10(1979)69-83.

Google Scholar

[6] J. Kautsky, N.K. Nichols and D.L.B. Jupp: Computer Vision, Graphics, and Image Processing. 26(1984)271-291.

DOI: 10.1016/0734-189x(84)90213-5

Google Scholar

[7] F.L. Gadallah, F. Csillag and J.M. Smithe: International Journal of Remote Sensing. 21(2000)2505-2511.

Google Scholar

[8] Wenbo Wu, Xun Zhang and Jing Chen: Remote sensing technology and application. 22(2007)722-726. (In Chinese)

Google Scholar

[9] Tao Chen, Xiaoli Xu and Shaohong Wang: Transactions of Beijing Institute of Technology. 30(2010)906-914. (In Chinese)

Google Scholar

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