Springer Multispectral Satellite Image Understanding: From Land Classification to Building and Road Detection (Advances in Computer Vision and Pattern Recognition)

This book presents a comprehensive review of image processing methods, for the analysis of land use in residential areas. Combining a theoretical framework with highly practical applications, the book describes a system for the effective detection of single houses and streets in very high resolution. Topics and features: with a Foreword by Prof. Dr. Peter Reinartz of the German Aerospace Center; provides end-of-chapter summaries and review questions; presents a detailed review on remote sensing satellites; examines the multispectral information that can be obtained from satellite images, with a focus on vegetation and shadow-water indices; investigates methods for land-use classification, introducing precise graph theoretical measures over panchromatic images; addresses the problem of detecting residential regions; describes a house and street network-detection subsystem; concludes with a summary of the key ideas covered in the book. Review From the reviews:“The authors write that their aims were the proposal of a novel automated end-to-end system to analyze multispectral satellite images and to emphasize how many research problems in remote sensing applications are waiting to be solved by the computer vision community. Well, the book satisfies both these goals. … it represents a good reference book, even a milestone, for teaching multispectral image understanding to students and/or young researchers.” (Primo Zingaretti, IAPR Newsletter, Vol. 34 (3), July-August, 2012) From the Back Cover Rapid development of remote sensing technology in recent years has greatly increased availability of high-resolution satellite image data.  However, detailed analysis of such large data sets also requires innovative new techniques in image and signal processing. This important text/reference presents a comprehensive review of image processing methods, for the analysis of land use in residential areas.  Combining a theoretical framework with highly practical applications, making use of both well-known methods and cutting-edge techniques in computer vision, the book describes a system for the effective detection of single houses and streets in very high resolution.  Topics and features: With a Foreword by Prof. Dr. Peter Reinartz of the German Aerospace Center Provides end-of-chapter summaries and review questions Presents a detailed review on remote sensing satellites Examines the multispectral information that can be obtained from satellite images, with a focus on vegetation and shadow-water indices Investigates methods for land-use classification, introducing precise graph theoretical measures over panchromatic images Addresses the problem of detecting residential regions Describes a house and street network-detection subsystem Concludes with a summary of the key ideas covered in the book This pioneering work on automated satellite and aerial image-understanding systems will be of great interest to researchers in both remote sensing and computer vision, highlighting the benefit of interdisciplinary collaboration between the two communities.  Urban planners and policy makers will also find considerable value in the proposed system. Dr. Cem Ünsalan is an Associate Professor in the Department of Electrical and Electronics Engineering at Yeditepe University, Istanbul, Turkey.  Dr. Kim Boyer is Professor and Head of the Department of Electrical, Computer, and Systems Engineering at Rensselaer Polytechnic Institute, Troy, NY, USA.