Buch, Englisch, 432 Seiten, Format (B × H): 183 mm x 260 mm, Gewicht: 1006 g
Buch, Englisch, 432 Seiten, Format (B × H): 183 mm x 260 mm, Gewicht: 1006 g
Reihe: Signal and Image Processing of Earth Observations
ISBN: 978-1-032-43741-5
Verlag: CRC Press
Advances in signal and image processing for remote sensing have been tremendous in recent years. The progress has been particularly significant with the use of deep learning based techniques to solve remote sensing problems. These advancements are the focus of this third edition of Signal and Image Processing for Remote Sensing. It emphasizes the use of machine learning approaches for the extraction of remote sensing information. Other topics include change detection in remote sensing and compressed sensing. With 19 new chapters written by world leaders in the field, this book provides an authoritative examination and offers a unique point of view on signal and image processing.
Features
- Includes all new content and does not replace the previous edition
- Covers machine learning approaches in both signal and image processing for remote sensing
- Studies deep learning methods for remote sensing information extraction that is found in other books
- Explains SAR, microwave, seismic, GPR, and hyperspectral sensors and all sensors considered
- Discusses improved pattern classification approaches and compressed sensing approaches
- Provides ample examples of each aspect of both signal and image processing
This book is intended for university academics, researchers, postgraduate students, industry, and government professionals who use remote sensing and its applications.
Zielgruppe
Postgraduate, Professional Reference, and Undergraduate Advanced
Autoren/Hrsg.
Fachgebiete
- Mathematik | Informatik EDV | Informatik Technische Informatik
- Geowissenschaften Umweltwissenschaften Umwelttechnik
- Geowissenschaften Geologie GIS, Geoinformatik
- Technische Wissenschaften Umwelttechnik | Umwelttechnologie Umwelttechnik
- Technische Wissenschaften Sonstige Technologien | Angewandte Technik Signalverarbeitung, Bildverarbeitung, Scanning
Weitere Infos & Material
PART I General Topics
Chapter 1 A Brief Overview of 60 Years of Progress on Signal/Image Processing for
Remote Sensing
C.H. Chen
Chapter 2 Proven Approaches of Using Innovative High-Performance Computing
Architectures in Remote Sensing
Rocco Sedona, Gabriele Cavallaro, Morris Riedel, and Jon Atli Benediktsson
PART II Signal Processing for Remote Sensing
Chapter 3 Machine Learning Techniques for Geophysical Parameter Retrievals
Adam B. Milstein, Michael Pieper, and William J. Blackwell
Chapter 4 Subsurface Inverse Profiling and Imaging Using Stochastic Optimization Techniques
Maryam Hajebi and Ahmad Hoorfar
Chapter 5 Close and Remote Ground Penetrating Radar Surveys via Microwave Tomography: State of Art and Perspectives
Gianluca Gennarelli, Giuseppe Esposito, Giovanni Ludeno,
Francesco Soldovieri, and Ilaria Catapano
Chapter 6 Polarimetric SAR Signature of Complex Scene: A Simulation Study
Kun-Shan Chen, Cheng-Yen Chiang, and Ying Yang
Chapter 7 Machine Learning for Arctic Sea Ice Physical Properties Estimation Using Dual-Polarimetric SAR Data
Katalin Blix, Martine M. Espeseth, and Torbjorn Eltoft
Chapter 8 Riemannian Clustering of PolSAR Data Using the Polar Decomposition
Madalina Ciuca, Gabriel Vasile, Marco Congedo, and Michel Gay
Chapter 9 Seismic Velocity Picking Using Hopfield Neural Network
Kou-Yuan Huang and Jia-Rong Yang
Chapter 10 Expanded Radial Basis Function Network with Proof of Hidden Node Number by Recurrence Relation for Well Log Data Inversion
Kou-Yuan Huang, Liang-Chi Shen, Jiun-Der You, and Li-Sheng Weng
PART III Image Processing for Remote Sensing
Chapter 11 Convolutional Neural Networks Meet Markov Random Fields for Semantic Segmentation of Remote Sensing Images
Martina Pastorino, Gabriele Moser, Sebastiano B. Serpico, and Josiane Zerubia
Chapter 12 Deep Learning Methods for Satellite Image Super-Resolution
Diego Valsesia and Enrico Magli
Chapter 13 Machine Learning in Remote Sensing
Ronny Hansch
Chapter 14 Robust Training of Deep Neural Networks with Weakly Labelled Data
Gianmarco Perantoni and Lorenzo Bruzzone
Chapter 15 Semantic Segmentation with OTBTF and Keras
Remi Cresson
Chapter 16 Performance of a Diffusion Model for Instance Segmentation in Remote Sensing Imagery
Selin Koles, Sedat Ozer, and C.H. Chen
Chapter 17 Land Cover Classification Using Attention-Based Multi-Modal Image Fusion: An Explainable Analysis
Oktay Karakus, Wanli Ma, and Paul L. Rosin
Chapter 18 FPGA Compressive Sensing Method Applied to Hyperspectral ImageryJose Nascimento and Mario Vestias
Chapter 19 Large-Scale Fine-Grained Change Detection from Multisensory Satellite Images
Andrea Garzelli and Claudia Zoppetti
Chapter 20 Change Detection on Graphs: Exploiting Graph Structure from Bi-temporal Satellite Imagery
Juan F. Florez-Ospina, Hernan D. Benitez-Restrepo, and David A. Jimenez-Sierra
Chapter 21 Target Detection in Hyperspectral Imaging Using Neural Networks
Edisanter Lo and Emmett Ientilucci