Noise Filtration in Hyperspectral Images

An approach to filtration of hyperspectral images corrupted by the Gaussian additive noise is proposed. The approach is based on using the property of interchannel redundancy of such images. The developed algorithm of noise filtration allows maintaining the contour and brightness portraits of object...

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Bibliographic Details
Published in:Optoelectronics, instrumentation, and data processing instrumentation, and data processing, 2020, Vol.56 (1), p.19-27
Main Author: Shipko, V. V.
Format: Article
Language:English
Subjects:
Analysis and Synthesis of Signals and Images
Lasers
Optical Devices
Optics
Photonics
Physics
Physics and Astronomy
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Summary:An approach to filtration of hyperspectral images corrupted by the Gaussian additive noise is proposed. The approach is based on using the property of interchannel redundancy of such images. The developed algorithm of noise filtration allows maintaining the contour and brightness portraits of objects in individual components of the hyperspectral image, in contrast to algorithms of linear component-by-component and vector filtration, as well as the algorithm of averaging over a set of components. The numerical results obtained in the study testify to the advantage provided by interchannel gradient reconstruction in terms of the accuracy of recovery of hyperspectral image components corrupted by additive noise. The efficiency of the proposed approach is demonstrated by an example of processing of real hyperspectral images.
ISSN:8756-6990
1934-7944
DOI:10.3103/S8756699020010033