Object Based Image Analysis

Download or read book Object-Based Image Analysis written by Thomas Blaschke and published by Springer Science & Business Media. This book was released on 2008-08-09 with total page 804 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book brings together a collection of invited interdisciplinary persp- tives on the recent topic of Object-based Image Analysis (OBIA). Its c- st tent is based on select papers from the 1 OBIA International Conference held in Salzburg in July 2006, and is enriched by several invited chapters. All submissions have passed through a blind peer-review process resulting in what we believe is a timely volume of the highest scientific, theoretical and technical standards. The concept of OBIA first gained widespread interest within the GIScience (Geographic Information Science) community circa 2000, with the advent of the first commercial software for what was then termed ‘obje- oriented image analysis’. However, it is widely agreed that OBIA builds on older segmentation, edge-detection and classification concepts that have been used in remote sensing image analysis for several decades. Nevert- less, its emergence has provided a new critical bridge to spatial concepts applied in multiscale landscape analysis, Geographic Information Systems (GIS) and the synergy between image-objects and their radiometric char- teristics and analyses in Earth Observation data (EO).

Download or read book Multispectral Image Analysis Using the Object-Oriented Paradigm written by Kumar Navulur and published by CRC Press. This book was released on 2006-12-05 with total page 206 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bringing a fresh new perspective to remote sensing, object-based image analysis is a paradigm shift from the traditional pixel-based approach. Featuring various practical examples to provide understanding of this new modus operandi, Multispectral Image Analysis Using the Object-Oriented Paradigm reviews the current image analysis methods and demonstrates advantages to improve information extraction from imagery. This reference describes traditional image analysis techniques, introduces object-oriented technology, and discusses the benefits of object-based versus pixel-based classification. It examines the creation of object primitives using image segmentation approaches and the use of various techniques for object classification. The author covers image enhancement methods, how to use ancillary data to constrain image segmentation, and concepts of semantic grouping of objects. He concludes by addressing accuracy assessment approaches. The accompanying downloadable resources present sample data that enable the use of different approaches to problem solving. Integrating remote sensing techniques and GIS analysis, Multispectral Image Analysis Using the Object-Oriented Paradigm distills new tools to extract information from remotely sensed data.

Download or read book Object-Based Image Analysis and Treaty Verification written by Sven Nussbaum and published by Springer Science & Business Media. This book was released on 2008-01-09 with total page 178 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes recent progress in object-based image interpretation. It presents new results in its application to verification of nuclear non-proliferation. A comprehensive workflow and newly developed algorithms for object-based high resolution image (pre-) processing, feature extraction, change detection, classification and interpretation are developed, applied and evaluated. The analysis chain is demonstrated with satellite imagery acquired over Iranian nuclear facilities.

Download or read book Assessing the Accuracy of Remotely Sensed Data written by Russell G. Congalton and published by CRC Press. This book was released on 2008-12-12 with total page 210 pages. Available in PDF, EPUB and Kindle. Book excerpt: Accuracy assessment of maps derived from remotely sensed data has continued to grow since the first edition of this groundbreaking book. As a result, the much-anticipated new edition is significantly expanded and enhanced to reflect growth in the field. The new edition features three new chapters, including: Fuzzy accuracy assessmentPositional accu

Download or read book Machine Learning Paradigms: Theory and Application written by Aboul Ella Hassanien and published by Springer. This book was released on 2018-12-08 with total page 472 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book focuses on machine learning. Divided into three parts, the first part discusses the feature selection problem. The second part then describes the application of machine learning in the classification problem, while the third part presents an overview of real-world applications of swarm-based optimization algorithms. The concept of machine learning (ML) is not new in the field of computing. However, due to the ever-changing nature of requirements in today’s world it has emerged in the form of completely new avatars. Now everyone is talking about ML-based solution strategies for a given problem set. The book includes research articles and expository papers on the theory and algorithms of machine learning and bio-inspiring optimization, as well as papers on numerical experiments and real-world applications.

Download or read book Picture Processing and Psychopictorics written by B.S. Lipkin and published by Elsevier. This book was released on 1970-01-01 with total page 535 pages. Available in PDF, EPUB and Kindle. Book excerpt: Picture Processing and Psychopictorics explores the selected aspects of perception and picture processing involving variables that are relevant to psychopictoric research. This book is organized into four parts encompassing 18 chapters. The first three parts cover the three classes of psychophysical variables, namely, contrast and border, shape and geometry, and texture. These parts also deal with the factors that influence the detection of objects in complex images. The discussion then shifts to the role of these factors in perception, as well as the computer analysis and manipulation of images with respect to these factors. The fourth part describes the programming systems for online experimental design and image manipulation. This work will be of great value to psychologists concerned with determining how the human extracts information from visual stimuli and to computer scientist concerned with developing programs and equipment to extract similar information from images.

Download or read book Hyperspectral Image Analysis written by Saurabh Prasad and published by Springer Nature. This book was released on 2020-04-27 with total page 464 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book reviews the state of the art in algorithmic approaches addressing the practical challenges that arise with hyperspectral image analysis tasks, with a focus on emerging trends in machine learning and image processing/understanding. It presents advances in deep learning, multiple instance learning, sparse representation based learning, low-dimensional manifold models, anomalous change detection, target recognition, sensor fusion and super-resolution for robust multispectral and hyperspectral image understanding. It presents research from leading international experts who have made foundational contributions in these areas. The book covers a diverse array of applications of multispectral/hyperspectral imagery in the context of these algorithms, including remote sensing, face recognition and biomedicine. This book would be particularly beneficial to graduate students and researchers who are taking advanced courses in (or are working in) the areas of image analysis, machine learning and remote sensing with multi-channel optical imagery. Researchers and professionals in academia and industry working in areas such as electrical engineering, civil and environmental engineering, geosciences and biomedical image processing, who work with multi-channel optical data will find this book useful.