Signal processing has been playing an increasingly important role in remote sensing,
though most remote sensing literatures are concerned with remote sensing images. Many
data received by remote sensors such as microwave and geophysical sensors, are signals or
waveforms, which can be processed by analog and digital signal processing techniques.
This volume is a spin-off edition derived from Signal and Image Processing for Remote
Sensing. It focuses on signal processing for remote sensing, and presents for the first time a
comprehensive and up-to-date treatment of the subject. The progress in signal processing
itself has been enormous in the last 30 years, but signal processing application in remote
sensing has received more attention only in recent years. This volume covers important
signal processing topics like principal component analysis, projected principal component
analysis, Kalman adaptive filtering, prediction error filtering for interpolation, factor
analysis, time series analysis, neural network classification, neural network parameter
retrieval, blind source separation algorithm, independent component analysis, etc. The
book presents for the first time the use of Huang–Hilbert transform in remote sensing
data. As there are so many areas in remote sensing that can benefit from signal processing,
we hope the book can help to attract more talents in signal processing to work on
remote sensing problems that may involve environmental monitoring, resource management
and planning, as well as energy exploration, and many others with the use of
remotely sensed data.
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.