Most data from satellites are in image form, thus most books in the remote sensing field deal exclusively with image processing. However, signal processing can contribute significantly in extracting information from the remotely sensed waveforms or time series data. Pioneering the combination of the two processes, Signal and Image Processing for Remote Sensing provides a balance between the role of signal processing and image processing in remote sensing.
Featuring contributions from worldwide experts, this book emphasizes mathematical approaches. Divided into two parts, Part I examines signal processing for remote sensing and Part II explores image processing. Not limited to the problems with data from satellite sensors, the book considers other sensors which acquire data remotely, including signals and images from infrasound, seismic, microwave, and satellite sensors. It covers a broader scope of issues in remote sensing information processing than other books in this area.
With rapid technological advances, the mathematical techniques provided will far outlast the sensor, software and hardware technologies. Focusing on methodologies of signal processing and image processing in remote sensing, this book discusses unique techniques for dealing with remote sensing problems.
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"...this book will be useful to advance automated image processing and the integration of remote sensor data with ecosystem and atmospheric models. The unique idea of combining signal processing with image processing is a good one and is well timed with ongoing technological advancements."
―Ross Lunetta, Remote Sensing Change Detection and Remote Sensing and GIS Accuracy Assessment
"Overall, the breadth and depth of content make this book an excellent reference for researchers, including graduate students, engaged in advanced remote sensing data analysis, who will find that some chapters provide inspiration to their own research."
―Qian Du, Department of Electrical and Computer Engineering, Mississippi State University, in Photogrammetric Engineering & Remote Sensing, Nov. 2007, Vol. 73, No. 11
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