Full-spectrum denoising of high-SNR hyperspectral images

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

2 Scopus Citations
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Detail(s)

Original languageEnglish
Pages (from-to)450-463
Journal / PublicationJournal of the Optical Society of America A: Optics and Image Science, and Vision
Volume36
Issue number3
Publication statusPublished - 1 Mar 2019
Externally publishedYes

Abstract

The high spectral redundancy of hyper/ultraspectral Earth-observation satellite imaging raises three challenges: (a) to design accurate noise estimation methods, (b) to denoise images with very high signal-to-noise ratio (SNR), and (c) to secure unbiased denoising. We solve (a) by a new noise estimation, (b) by a novel Bayesian algorithm exploiting spectral redundancy and spectral clustering, and (c) by accurate measurements of the interchannel correlation after denoising. We demonstrate the effectiveness of our method on two ultraspectral Earth imagers, IASI and IASI-NG, one flying and the other in project, and sketch the major resolution gain of future instruments entailed by such unbiased denoising. © 2019 Optical Society of America.

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