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Signal Processing for Remote Sensing

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Overview

Written by leaders in the field, Signal Processing for Remote Sensing explores the data acquisitions segment of remote sensing. Each chapter presents a major research result or the most up to date development of a topic. The book includes a chapter by Dr. Norden Huang, inventor of the Huang-Hilbert transform who, along with and Dr. Steven Long discusses the application of the transform to remote sensing problems. It also contains a chapter by Dr. Enders A. Robinson, who has made major contributions to seismic signal processing for over half a century, on the basic problem of constructing seismic images by ray tracing.

With rapid technological advances in both sensor and processing technologies, a book can only capture the current process and result. However, the numerous mathematical techniques provided in this book have lasting value, giving it a useful role for many years to come. While the majority of remote sensing titles cover only image processing, this book focuses on the data acquisitions segment of remote sensing. Its uniquely specific and practical approach allows you to directly apply the knowledge in this book to your field of remote sensing applications.

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Product Details

  • ISBN-13: 9781420066661
  • Publisher: CRC Press
  • Publication date: 10/10/2007
  • Edition description: Reissue
  • Pages: 280
  • Product dimensions: 7.00 (w) x 9.90 (h) x 0.90 (d)

Table of Contents

Contents
On the Normalized Hilbert Transform and Its Applications in Remote Sensing, S.R. Long and N.E. Huang
Statistical Pattern Recognition and Signal Processing in Remote Sensing, C.H. Chen
A Universal Neural Network—Based Infrasound Event Classifier, F.M. Ham and R. Acharyya
Construction of Seismic Images by Ray Tracing, E.A. Robinson
Multi-Dimensional Seismic Data Decomposition by Higher Order SVD and Unimodal ICA, N. Le Bihan, V. Vrabie, and J.I. Mars
Application of Factor Analysis in Seismic Profiling, Z. Wang and C.H. Chen
Kalman Filtering for Weak Signal Detection in Remote Sensing, S.L. Tantum, Y. Tan, and L.M. Collins
Relating Time-Series of Meteorological and Remote Sensing Indices to Monitor Vegetation Moisture Dynamics, J. Verbesselt, P. Jönsson, S. Lhermitte, I. Jonckheere, J. van Aardt, and P. Coppin
Use of a Prediction-Error Filter in Merging High- and Low-Resolution Images, S.-H. Yun and H. Zebker
Blind Separation of Convolutive Mixtures for Canceling Active Sonar Reverberation, F. Cong, C.H. Chen, S. Ji, P. Jia, and X. Shi
Neural Network Retrievals of Atmospheric Temperature and Moisture Profiles from High-Resolution Infrared and Microwave Sounding Data, W.J. Blackwell
Satellite-Based Precipitation Retrieval Using Neural Networks, Principal Component Analysis, and Image Sharpening, F.W. Chen

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