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Proceedings Paper

Residual-scaled local standard deviations method for estimating noise in hyperspectral images
Author(s): Lianru Gao; Jianting Wen; Qiong Ran
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Paper Abstract

A new method for estimating noise in hyperspectral images is described in this paper. It is based on the strong between-band correlation of hyperspectral images and the concept of local standard deviations of small imaging blocks. The new method can be used to automatically estimate noise for both radiance and reflectance images. Unlike other methods discussed in this paper, the new method is more reliable for estimating noise in hyperspectral images with diverse land cover types. We successfully applied the new method in estimating noise for Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data.

Paper Details

Date Published: 15 November 2007
PDF: 9 pages
Proc. SPIE 6787, MIPPR 2007: Multispectral Image Processing, 678713 (15 November 2007); doi: 10.1117/12.749122
Show Author Affiliations
Lianru Gao, Institute of Remote Sensing Applications (China)
Jianting Wen, Institute of Remote Sensing Applications (China)
Qiong Ran, Institute of Remote Sensing Applications (China)


Published in SPIE Proceedings Vol. 6787:
MIPPR 2007: Multispectral Image Processing

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