Provides in-depth coverage of novel computer vision methods for remote sensing applications
Includes end-of-chapter summaries and review questions
With a Foreword by Prof. Dr. Peter Reinartz of the German Aerospace Center
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.|
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.
Introduction
Part I: Sensors
Remote Sensing Satellites and Airborne Sensors
Part II: The Multispectral Information
Linearized Vegetation Indices
Linearized Shadow and Water Indices
Part III: Land Use Classification
Review on Land Use Classification
Land Use Classification using Structural Features
Land Use Classification via Multispectral Information
Graph Theoretical Measures for Land Development
Part IV: Extracting Residential Regions
Feature Based Grouping to Detect Suburbia
Detecting Residential Regions by Graph Theoretical Measures
Part V: Building and Road Detection
Review on Building and Road Detection
House and Street Network Detection in Residential Regions
Part VI: Summarizing the Overall System
Final Comments
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.
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)
Covering image processing methods for analyzing residential land use, this book combines theoretical framework with practical applications, and describes a high resolution system for effective detection of single houses, vegetation and shadow-water indices.
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)
Inhaltsverzeichnis
Introduction
Part I: Sensors
Remote Sensing Satellites and Airborne Sensors
Part II: The Multispectral Information
Linearized Vegetation Indices
Linearized Shadow and Water Indices
Part III: Land Use Classification
Review on Land Use Classification
Land Use Classification using Structural Features
Land Use Classification via Multispectral Information
Graph Theoretical Measures for Land Development
Part IV: Extracting Residential Regions
Feature Based Grouping to Detect Suburbia
Detecting Residential Regions by Graph Theoretical Measures
Part V: Building and Road Detection
Review on Building and Road Detection
House and Street Network Detection in Residential Regions
Part VI: Summarizing the Overall System
Final Comments
Klappentext
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.
Provides in-depth coverage of novel computer vision methods for remote sensing applications
Includes end-of-chapter summaries and review questions
With a Foreword by Prof. Dr. Peter Reinartz of the German Aerospace Center
Includes supplementary material: sn.pub/extras