Real-Time Recursive Hyperspectral Sample and Band Processing : Algorithm Architecture and Implementation /

This book explores recursive architectures in designing progressive hyperspectral imaging algorithms. In particular, it makes progressive imaging algorithms recursive by introducing the concept of Kalman filtering in algorithm design so that hyperspectral imagery can be processed not only progressiv...

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Bibliographic Details
Main Author: Chang, Chein-I (Author)
Format: Electronic eBook
Language:English
Published: Cham : Springer International Publishing : Imprint: Springer, 2017.
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Summary:This book explores recursive architectures in designing progressive hyperspectral imaging algorithms. In particular, it makes progressive imaging algorithms recursive by introducing the concept of Kalman filtering in algorithm design so that hyperspectral imagery can be processed not only progressively sample by sample or band by band but also recursively via recursive equations. This book can be considered a companion book of author’s books, Real-Time Progressive Hyperspectral Image Processing, published by Springer in 2016. Explores recursive structures in algorithm architecture Implements algorithmic recursive architecture in conjunction with progressive sample and band processing Derives Recursive Hyperspectral Sample Processing (RHSP) techniques according to Band-Interleaved Sample/Pixel (BIS/BIP) acquisition format Develops Recursive Hyperspectral Band Processing (RHBP) techniques according to Band SeQuential (BSQ) acquisition format for hyperspectral data.
Physical Description:1 online resource.
ISBN:9783319451718
DOI:10.1007/978-3-319-45171-8