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Titlebook: Object-Based Image Analysis; Spatial Concepts for Thomas Blaschke (Prof.),Stefan Lang (Dr.),Geoffrey Book 20081st edition Springer-Verlag B

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发表于 2025-3-21 19:47:50 | 显示全部楼层 |阅读模式
书目名称Object-Based Image Analysis
副标题Spatial Concepts for
编辑Thomas Blaschke (Prof.),Stefan Lang (Dr.),Geoffrey
视频video
概述Discusses means, technologies and approaches related to the processing and analysis of multi-sensor, multi-resolution data with a focus on the generation, modelling and classification of objects.Inclu
丛书名称Lecture Notes in Geoinformation and Cartography
图书封面Titlebook: Object-Based Image Analysis; Spatial Concepts for Thomas Blaschke (Prof.),Stefan Lang (Dr.),Geoffrey Book 20081st edition Springer-Verlag B
描述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).
出版日期Book 20081st edition
关键词Change detection; GIS; Geoinformationssysteme; IKONOS; Monitoring; Object-based image analysis; classifica
版次1
doihttps://doi.org/10.1007/978-3-540-77058-9
isbn_softcover978-3-662-50146-7
isbn_ebook978-3-540-77058-9Series ISSN 1863-2246 Series E-ISSN 1863-2351
issn_series 1863-2246
copyrightSpringer-Verlag Berlin Heidelberg 2008
The information of publication is updating

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发表于 2025-3-21 22:35:35 | 显示全部楼层
Progressing from object-based to object-oriented image analysisally a segmentation step is followed by a classification step, a new workflow is illustrated where the objects themselves are altered constantly in order to move from object primitives in an early stage towards objects of interest in a final stage of the analysis. Consequently, this workflow can be
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Image objects and geographic objectserous successful case studies, little effort has been directed towards building the conceptual foundations underlying it. In particular, there are at least two questions that need a clear answer before OBIA can be considered a discipline: i) What is the definition and ontological status of both imag
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Using texture to tackle the problem of scale in land-cover classificationl imagery. We argue that in many of its current implementations, OBIA is not an accurate model of this system. Drawing from current theories in cognitive psychology, we propose a new conceptual model which we believe more accurately represents how the HVS performs aerial image interpretation. The fi
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Domain-specific class modelling for one-level representation of single treesthe specific scale domains of the target features addressed. Two near-natural forest settings served as testing environment for a combined use of airborne laser scanning (ALS) and optical image data to perform automated tree-crown delineation. The primary methodological aim was to represent the enti
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Object recognition and image segmentation: the Feature Analyst® approachve problem in the maintenance cycle of a Geographic Information System (GIS). Traditional collection methods, such as hand-digitizing, are slow, tedious and cannot keep up with the ever-increasing volume of imagery assets. In this paper we describe the methodology underlying the Feature Analyst auto
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A procedure for automatic object-based classificationThe emerging object-based methodology for image classification appears to be a better way to mimic the human thought process. Unlike pixel-based techniques which only use the layer pixel values, the object-based techniques can also use shape and context information of a scene texture. These extra de
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