Remote Sensing Data Compression

ISBN 10: 3036523030 / ISBN 13: 9783036523033

Published by MDPI AG, 2021

About this Item

Remote Sensing Data Compression | Buch | Gebunden | Englisch | 2021 | MDPI AG | EAN 9783036523033 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.

Seller Inventory # 120919891

Bibliographic Details

• Title: Remote Sensing Data Compression
• Publisher: MDPI AG
• Publication Date: 2021
• Language: English
• ISBN 10: 3036523030
• ISBN 13: 9783036523033
• Binding: Buch
• Condition: Neu
• Dimensions: 250W x 175H x 28D millimeters 250 millimeters width by 175 millimeters height by 28 millimeters depth
• Weight: 1114 grams
• Seller catalogs:
  • Bücher

About this title

Synopsis

A huge amount of data is acquired nowadays by different remote sensing systems installed on satellites, aircrafts, and UAV. The acquired data then have to be transferred to image processing centres, stored and/or delivered to customers. In restricted scenarios, data compression is strongly desired or necessary. A wide diversity of coding methods can be used, depending on the requirements and their priority. In addition, the types and properties of images differ a lot, thus, practical implementation aspects have to be taken into account. The Special Issue paper collection taken as basis of this book touches on all of the aforementioned items to some degree, giving the reader an opportunity to learn about recent developments and research directions in the field of image compression. In particular, lossless and near-lossless compression of multi- and hyperspectral images still remains current, since such images constitute data arrays that are of extremely large size with rich information that can be retrieved from them for various applications. Another important aspect is the impact of lossless compression on image classification and segmentation, where a reasonable compromise between the characteristics of compression and the final tasks of data processing has to be achieved. The problems of data transition from UAV-based acquisition platforms, as well as the use of FPGA and neural networks, have become very important. Finally, attempts to apply compressive sensing approaches in remote sensing image processing with positive outcomes are observed. We hope that readers will find our book useful and interesting.