Residual-scaled local standard deviations method for estimating noise in hyperspectral images

Lianru Gao; Jianting Wen; Qiong Ran

doi:10.1117/12.749122

15 November 2007 Residual-scaled local standard deviations method for estimating noise in hyperspectral images

Lianru Gao, Jianting Wen, Qiong Ran

Proceedings Volume 6787, MIPPR 2007: Multispectral Image Processing; 678713 (2007) https://doi.org/10.1117/12.749122
Event: International Symposium on Multispectral Image Processing and Pattern Recognition, 2007, Wuhan, China

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.

Citation Download Citation

Lianru Gao, Jianting Wen, and Qiong Ran "Residual-scaled local standard deviations method for estimating noise in hyperspectral images", Proc. SPIE 6787, MIPPR 2007: Multispectral Image Processing, 678713 (15 November 2007); https://doi.org/10.1117/12.749122

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