Page Comparison

Chein-I Chang, Ed., Recent Advances in Hyperspectral Signal and Image Processing, Research Signpost, Trasworld Research Network, India, 2006

Preface: Preface_new.pdf Frontcover: cover.pdf.pdf Brochure: brochure.pdf

This book is a collection of 16 chapters written by leading experts in their respective areas. It is made up of two parts, Part I: 6 chapters contributed by the Remote Sensing Signal and Image Processing Laboratory (RSSIPL) at the University of Maryland, and Part II: 10 chapters contributed by researchers from other organizations. The chapters presented in the book offer readers with a broad view of hyperspectral signal and image processing. The book will serve as a valuable and useful reference for researchers in academia and practitioners in government and industry.

Chein-I Chang, Ed., Hyperspectral Data Exploitation: Theory and Applications, John Wiley & Sons, 2007

Overview: c010.pdf    Frontcover: frontcover_HDE.pdf

Authored by a panel of experts in the field, this book focuses on hyperspectral image analysis, systems, and applications. With discussion of application-based projects and case studies, this professional reference will bring you up-to-date on this pervasive technology, wether you are working in the military and defense fields, or in remote sensing technology, geoscience, or agriculture.Authored by a panel of experts in the field, this book focuses on hyperspectral image analysis, systems, and applications. With discussion of application-based projects and case studies, this professional reference will bring you up-to-date on this pervasive technology, wether you are working in the military and defense fields, or in remote sensing technology, geoscience, or agriculture.

A. Plaza and Chein-I Chang, Ed., High Performance Computing in Remote Sensing, Chapman & Hall/CRC Press, 2007.

cover:C6625_Cover.pdf  Preface: Chapter01_preface_finished.pdf

The recent use of latest-generation sensors in airborne and satellite platforms is producing a nearly continual stream of high-dimensional data, which, in turn, is creating new processing challenges. To address the computational requirements of time-critical applications, researchers have begun incorporating high performance computing (HPC) models in remote sensing missions. High Performance Computing in Remote Sensing is one of the first volumes to explore state-of-the-art HPC techniques in the context of remote sensing problems. It focuses on the computational complexity of algorithms that are designed for parallel computing and processing.

The book first addresses key computing concepts and developments in remote sensing. It also covers application areas not necessarily related to remote sensing, such as multimedia and video processing. Each subsequent chapter illustrates a specific parallel computing paradigm, including multiprocessor (cluster-based) systems, large-scale and heterogeneous networks of computers, grid computing platforms, and specialized hardware architectures for remotely sensed data analysis and interpretation.

The extensive reviews of current and future developments combined with thoughtful perspectives on the potential challenges of adapting HPC paradigms to remote sensing problems will undoubtedly foster collaboration and development among many fields.