Processing and Analysis of Hyperspectral Data

Jie Chen

ISBN 10: 1789851092 / ISBN 13: 9781789851090

Published by Intechopen Jan 2020, 2020

About this Item

This item is printed on demand - Print on Demand Titel. Neuware -Hyperspectral imagery has received considerable attention in the last decade as it provides rich spectral information and allows the analysis of objects that are unidentifiable by traditional imaging techniques. It has a wide range of applications, including remote sensing, industry sorting, food analysis, biomedical imaging, etc. However, in contrast to RGB images from which information can be intuitively extracted, hyperspectral data is only useful with proper processing and analysis. This book covers theoretical advances of hyperspectral image processing and applications of hyperspectral processing, including unmixing, classification, super-resolution, and quality estimation with classical and deep learning methods.Books on Demand GmbH, Überseering 33, 22297 Hamburg 136 pp. Englisch.

Seller Inventory # 9781789851090

Bibliographic Details

• Title: Processing and Analysis of Hyperspectral Data
• Publisher: Intechopen Jan 2020
• Publication Date: 2020
• Language: English
• ISBN 10: 1789851092
• ISBN 13: 9781789851090
• Binding: Buch
• Condition: Neu
• Dimensions: 266W x 185H x 14D millimeters 266 millimeters width by 185 millimeters height by 14 millimeters depth
• Weight: 515 grams

About this title

Synopsis

Hyperspectral imagery has received considerable attention in the last decade as it provides rich spectral information and allows the analysis of objects that are unidentifiable by traditional imaging techniques. It has a wide range of applications, including remote sensing, industry sorting, food analysis, biomedical imaging, etc. However, in contrast to RGB images from which information can be intuitively extracted, hyperspectral data is only useful with proper processing and analysis. This book covers theoretical advances of hyperspectral image processing and applications of hyperspectral processing, including unmixing, classification, super-resolution, and quality estimation with classical and deep learning methods.