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Proceedings Paper

Image and spectral fidelity study of hyperspectral remote sensing image scaling up based on wavelet transform
Author(s): Ni An; Yi Ma; Yuhai Bao
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Paper Abstract

Wavelet transform is a kind of effective image-scale transformation method, which can achieve multi-scale transformation by distinguishing the low-frequency information and the high-frequency information. Hyperspectral remote sensing data combining image with spectrum has almost continuous spectrum that is the important premise of extracting hyperspectral image information, while scale transformation will inevitably lead to the change of image and spectra. Therefore, it is important to study the image and spectral fidelity after wavelet transform. In this paper, the Proba CHRIS hyperspectral remote sensing image of Yellow River Estuary Wetland is used to investigate the image and spectral fidelity of image transformed by wavelet which remained the low-frequency information. The level 1-3 of up-scale images are obtained and then compared with the original. Then image and spectral fidelity is quantitatively analyzed. The results show that the image fidelity is slightly reduced by up-scale transformation, but near-infrared images have a larger distortion than other bands. With the increasing scaling up, the distortion of spectrum is more and more great, but spectral fidelity is overall well. For the typical wetland objects, Phragmites austrialis has the best spectral correlation, Spartina has a small spectra change, and aquaculture water spectral distortion is most remarkable.

Paper Details

Date Published: 6 August 2015
PDF: 8 pages
Proc. SPIE 9669, Remote Sensing of the Environment: 19th National Symposium on Remote Sensing of China, 96690A (6 August 2015); doi: 10.1117/12.2204853
Show Author Affiliations
Ni An, State Oceanic Administration (China)
Inner Mongolia Normal Univ. (China)
Yi Ma, State Oceanic Administration (China)
Inner Mongolia Normal Univ. (China)
Yuhai Bao, Inner Mongolia Normal Univ. (China)

Published in SPIE Proceedings Vol. 9669:
Remote Sensing of the Environment: 19th National Symposium on Remote Sensing of China
Qingxi Tong; Boqin Zhu, Editor(s)

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