[PDF] Full Image Segmentation For Environmental Monitoring Download eBook

Image Segmentation for Environmental Monitoring

Author: Brian Alan Johnson

Publisher: MDPI

Published: 2020-12-02

Total Pages: 198

ISBN-13: 3039364774

OBIA, based on image segmentation and as an important remote sensing monitoring technology, has been widely used in forestry, vegetation, wetland, urban, crop, conservation, ecology, and agriculture areas. Although OBIA has considerably progressed in the past 20 years, OBIA still much room for further development, regardless of the technological aspect of OBIA or the prospective expansion field of applications. Therefore, this book was organized to further encourage OBIA technology development and expand OBIA applications. This book collects a total of eight papers, which compile the current state-of-the-art research and technology in the area of image segmentation, and highlight prominent current application directions. Therefore, this book not only contains innovative methods, but also covers the innovation of application-driven OBIA technology. The eight papers in this highlight both the popular applications (urban, vegetation, ecology) and several subjects that require additional research attention (landslide, arid-land).

Image Segmentation

Author: Pei-Gee Ho

Publisher: BoD – Books on Demand

Published: 2011-04-19

Total Pages: 554

ISBN-13: 9533072288

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It was estimated that 80% of the information received by human is visual. Image processing is evolving fast and continually. During the past 10 years, there has been a significant research increase in image segmentation. To study a specific object in an image, its boundary can be highlighted by an image segmentation procedure. The objective of the image segmentation is to simplify the representation of pictures into meaningful information by partitioning into image regions. Image segmentation is a technique to locate certain objects or boundaries within an image. There are many algorithms and techniques have been developed to solve image segmentation problems, the research topics in this book such as level set, active contour, AR time series image modeling, Support Vector Machines, Pixon based image segmentations, region similarity metric based technique, statistical ANN and JSEG algorithm were written in details. This book brings together many different aspects of the current research on several fields associated to digital image segmentation. Four parts allowed gathering the 27 chapters around the following topics: Survey of Image Segmentation Algorithms, Image Segmentation methods, Image Segmentation Applications and Hardware Implementation. The readers will find the contents in this book enjoyable and get many helpful ideas and overviews on their own study.

Object-Based Image Analysis

Author: Thomas Blaschke

Publisher: Springer Science & Business Media

Published: 2008-08-09

Total Pages: 804

ISBN-13: 3540770585

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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).

Environmental Monitoring and Characterization

Author: Janick Artiola

Publisher: Elsevier

Published: 2004-06-10

Total Pages: 425

ISBN-13: 0080491278

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Environmental Monitoring and Characterization is an integrated, hands-on resource for monitoring all aspects of the environment. Sample collection methods and relevant physical, chemical and biological processes necessary to characterize the environment are brought together in twenty chapters which cover: sample collection methods, monitoring terrestrial, aquatic and air environments, and relevant chemical, physical and biological processes and contaminants. This book will serve as an authoritative reference for advanced students and environmental professionals. - Examines the integration of physical, chemical, and biological processes - Emphasizes field methods and real-time data acquisition, made more accessible with case studies, problems, calculations, and questions - Includes four color illustrations throughout the text - Brings together the concepts of environmental monitoring and site characterization

Hyperspectral Remote Sensing

Author: Marcus Borengasser

Publisher: CRC Press

Published: 2007-12-13

Total Pages: 130

ISBN-13: 1420012606

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Land management issues, such as mapping tree species, recognizing invasive plants, and identifying key geologic features, require an understanding of complex technical issues before the best decisions can be made. Hyperspectral remote sensing is one the technologies that can help with reliable detection and identification. Presenting the fundamenta

Digital Image Processing

Author: Mr. Bandam Narendar

Publisher: RK Publication

Published: 2024-06-21

Total Pages: 301

ISBN-13: 8197469776

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Digital Image Processing the fundamentals and advanced techniques used to analyze, enhance, and transform digital images. It covers key concepts like image representation, filtering, segmentation, restoration, and compression. This both the theoretical foundations and practical applications of image processing, making it suitable for students and professionals in fields such as computer science, engineering, and applied sciences. With a balance of algorithms, examples, and visual illustrations, it provides readers with a comprehensive understanding of how digital images are processed and utilized in modern technology.

Image Segmentation

Author: Tao Lei

Publisher: John Wiley & Sons

Published: 2022-09-26

Total Pages: 340

ISBN-13: 1119859034

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Image Segmentation Summarizes and improves new theory, methods, and applications of current image segmentation approaches, written by leaders in the field The process of image segmentation divides an image into different regions based on the characteristics of pixels, resulting in a simplified image that can be more efficiently analyzed. Image segmentation has wide applications in numerous fields ranging from industry detection and bio-medicine to intelligent transportation and architecture. Image Segmentation: Principles, Techniques, and Applications is an up-to-date collection of recent techniques and methods devoted to the field of computer vision. Covering fundamental concepts, new theories and approaches, and a variety of practical applications including medical imaging, remote sensing, fuzzy clustering, and watershed transform. In-depth chapters present innovative methods developed by the authors—such as convolutional neural networks, graph convolutional networks, deformable convolution, and model compression—to assist graduate students and researchers apply and improve image segmentation in their work. Describes basic principles of image segmentation and related mathematical methods such as clustering, neural networks, and mathematical morphology. Introduces new methods for achieving rapid and accurate image segmentation based on classic image processing and machine learning theory. Presents techniques for improved convolutional neural networks for scene segmentation, object recognition, and change detection, etc. Highlights the effect of image segmentation in various application scenarios such as traffic image analysis, medical image analysis, remote sensing applications, and material analysis, etc. Image Segmentation: Principles, Techniques, and Applications is an essential resource for undergraduate and graduate courses such as image and video processing, computer vision, and digital signal processing, as well as researchers working in computer vision and image analysis looking to improve their techniques and methods.