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.
Reviews / Votes
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)
Series
Edition
Language
Place of publication
Target group
Professional and scholarly
Research
Illustrations
Dimensions
Height: 235 mm
Width: 155 mm
Thickness: 12 mm
Weight
ISBN-13
978-1-4471-2656-0 (9781447126560)
DOI
10.1007/978-0-85729-667-2
Schweitzer Classification
Cem Ünsalan is a full professor at the Department of Electrical and Electronics Engineering at Yeditepe University, Turkey, since 2013. He is the Dean of the Faculty of Engineering at the same university. Dr. Ünsalan also worked as a full professor at the Department of Electrical and Electronics Engineering at Marmara University, Turkey, between 2017 and 2023. He served as the department head for four years there. Dr. Ünsalan received his BSc degree from Hacettepe University, Turkey, his MSc degree from Bogazici University, Turkey, and his Ph.D. from The Ohio State University, USA, in 1995, 1998, and 2003, respectively. His research focuses on embedded systems, computer vision, and remote sensing. He has published extensively on these topics in respected journals and has written several books, including Embedded System Design with ARM Cortex-M Microcontrollers: Applications with C, C++ and MicroPython (Springer, 2022).
Berkan Höke is currently working as a senior machine vision engineer at Agsenze Ltd, United Kingdom. He has a diverse professional background including roles as a computer vision engineer at Migros, Turkey (2017-2020), machine learning engineer at Huawei, Turkey (2020-2022), and computer vision engineer at Techsign, Turkey (2022-2023). Mr. Höke received his BSc degree from Bilkent University, Turkey, and his MSc degree from Böaziçi University, Turkey, in 2014 and 2019, respectively. His research focuses on machine learning, computer vision, and embedded systems.
Eren Atmaca is currently pursuing his master's degree in communications and electronics engineering at Technical University of Munich, Germany. He received his bachelor's degree from Marmara University, Turkey in 2022. His research focuses on embedded systems, signal processing, and machine learning.
