The remote sensing area has experienced rapid growth in recent years. One major factor that impacts the growth is the numerous signal and image processing techniques, as well as progress in pattern recognition, artificial intelligence, computer vision, etc. There has been much improvement in computer software and hardware making the use of signal and image processing with the earth observation data much more feasible. With major advances in the development of remote sensing sensors and devices in recent years, the need for advanced information extraction techniques is quite evident. This book series highlights various aspects of signal and image processing activities on earth observations. Mathematical techniques and system developments incorporating signal and image processing in remote sensing is the focus of the series.
Edited
By C.H. Chen
June 11, 2024
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...
By Rémi Cresson
January 16, 2022
In today’s world, deep learning source codes and a plethora of open access geospatial images are readily available and easily accessible. However, most people are missing the educational tools to make use of this resource. Deep Learning for Remote Sensing Images with Open Source Software is the ...
By Qin Zhang, Roger Skjetne
February 16, 2018
Sea Ice Image Processing with MATLAB addresses the topic of image processing for the extraction of key sea ice characteristics from digital photography, which is of great relevance for Artic remote sensing and marine operations. This valuable guide provides tools for quantifying the ice environment...
By Fabrizio Berizzi, Marco Martorella, Elisa Giusti
February 12, 2018
Based on the experiences of the Department of Information Engineering of the University of Pisa and the Radar and Surveillance System (RaSS) national laboratory of the National Interuniversity Consortium of Telecommunication (CNIT), Radar Imaging for Maritime Observation presents the most recent ...
Edited
By C.H. Chen
June 01, 2017
Future remote sensing systems will make extensive use of Compressive Sensing (CS) as it becomes more integrated into the system design with increased high resolution sensor developments and the rising earth observation data generated each year. Written by leading experts in the field Compressive ...
By Kun-Shan Chen
December 18, 2015
Principles of Synthetic Aperture Radar Imaging: A System Simulation Approach demonstrates the use of image simulation for SAR. It covers the various applications of SAR (including feature extraction, target classification, and change detection), provides a complete understanding of SAR principles, ...
By Luciano Alparone, Bruno Aiazzi, Stefano Baronti, Andrea Garzelli
March 06, 2015
A synthesis of more than ten years of experience, Remote Sensing Image Fusion covers methods specifically designed for remote sensing imagery. The authors supply a comprehensive classification system and rigorous mathematical description of advanced and state-of-the-art methods for pansharpening of...
Edited
By C.H. Chen
February 22, 2012
Continuing in the footsteps of the pioneering first edition, Signal and Image Processing for Remote Sensing, Second Edition explores the most up-to-date signal and image processing methods for dealing with remote sensing problems. Although most data from satellites are in image form, signal ...