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Proceedings Paper

A new method of remote sensing image recovery based on WWC
Author(s): Xifang Zhu; Feng Wu; ChunKan Tao
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Paper Abstract

By analyzing the multi-resolution characteristics of wavelet series, the frequency distribution of detail and approximation coefficients is deduced. It is concluded that the frequency of detail coefficients in low levels is higher than that in high levels, and the frequency of approximation coefficients is the lowest. According to this conclusion, this paper proposes a new method of remote sensing image recovery based on Weighted Wavelet Coefficient (WWC), namely, removing the cloud and mist from the remote sensing images using weighted wavelet coefficient algorithm. Suppose the image is decomposed by η levels with wavelet transform. By choosing reasonable level number l, the scenery information is mainly distributed to 1~l levels where detail coefficients have lower frequency and cloud and mist noise information are distributed mainly to l~n; levels where detail coefficients have relatively higher frequency. Approximation coefficients will also include cloud information. Detail coefficients in low levels and high levels and approximation coefficients are weighted with different factors. The scenery information is enhanced by increasing detail coefficients in low levels with a weight great than 1. The cloud and mist noise is weakened by decreasing detail coefficients in high levels with a weight less than 1. Approximation coefficients are weighted appropriately if including cloud. It is also proposed that the information entropy is taken as a criterion for choosing the number of the demarcation levels and the weighted factors. We have confirmed that our new algorithm is better than homomorphism filtering and Retinex algorithm by experiments.

Paper Details

Date Published: 28 January 2009
PDF: 8 pages
Proc. SPIE 7156, 2008 International Conference on Optical Instruments and Technology: Optical Systems and Optoelectronic Instruments, 71561P (28 January 2009); doi: 10.1117/12.806585
Show Author Affiliations
Xifang Zhu, Changzhou Institute of Technology (China)
Nanjing Univ. of Science and Technology (China)
Feng Wu, Changzhou Institute of Technology (China)
ChunKan Tao, Nanjing Univ. of Science and Technology (China)


Published in SPIE Proceedings Vol. 7156:
2008 International Conference on Optical Instruments and Technology: Optical Systems and Optoelectronic Instruments

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