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25 October 2016 Estimate the noise of high-spectral data with multiplicative noise model
Lijiang Zhu, Dongsheng Gao, Yanjie Yang
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Proceedings Volume 10156, Hyperspectral Remote Sensing Applications and Environmental Monitoring and Safety Testing Technology; 101561O (2016) https://doi.org/10.1117/12.2247284
Event: International Symposium on Optoelectronic Technology and Application 2016, 2016, Beijing, China
Abstract
The multiplicative noise model for HS data cube was introduced in this paper. Based on this model, an algorithm was also developed to estimate the noise of the HS data in spatial and spectral domain. The comparison among the classical additive noise model, Poisson noise model and multiplicative was also discussed. The noise estimation experiments show that the multiplicative noise model is reasonable and suitable for HS data. The good performance of the NSR algorithms validated the effectiveness of the multiplicative noise model. The experiments also show that the multiplicative noise model have unique characteristics in information extraction of land cover. Based on the Multiplicative Noise model, we found that some natural objects like waters can be easily distinguished and extracted from the HS data using the NSR algorithm that we proposed in this study.
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Lijiang Zhu, Dongsheng Gao, and Yanjie Yang "Estimate the noise of high-spectral data with multiplicative noise model", Proc. SPIE 10156, Hyperspectral Remote Sensing Applications and Environmental Monitoring and Safety Testing Technology, 101561O (25 October 2016); https://doi.org/10.1117/12.2247284
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Data modeling
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