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001 978-0-85729-667-2
003 DE-He213
005 20140220083714.0
007 cr nn 008mamaa
008 130531s2011 xxk| s |||| 0|eng d
020 _a9780857296672
_9978-0-85729-667-2
024 7 _a10.1007/978-0-85729-667-2
_2doi
050 4 _aTA1637-1638
050 4 _aTA1637-1638
072 7 _aUYT
_2bicssc
072 7 _aUYQV
_2bicssc
072 7 _aCOM012000
_2bisacsh
072 7 _aCOM016000
_2bisacsh
082 0 4 _a006.6
_223
082 0 4 _a006.37
_223
100 1 _aÜnsalan, Cem.
_eauthor.
245 1 0 _aMultispectral Satellite Image Understanding
_h[electronic resource] :
_bFrom Land Classification to Building and Road Detection /
_cby Cem Ünsalan, Kim L. Boyer.
264 1 _aLondon :
_bSpringer London :
_bImprint: Springer,
_c2011.
300 _aXVIII, 186 p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aAdvances in Computer Vision and Pattern Recognition,
_x2191-6586
505 0 _aIntroduction -- 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.
520 _aRapid 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.
650 0 _aComputer science.
650 0 _aComputer vision.
650 0 _aOptical pattern recognition.
650 1 4 _aComputer Science.
650 2 4 _aImage Processing and Computer Vision.
650 2 4 _aPattern Recognition.
700 1 _aBoyer, Kim L.
_eauthor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9780857296665
830 0 _aAdvances in Computer Vision and Pattern Recognition,
_x2191-6586
856 4 0 _uhttp://dx.doi.org/10.1007/978-0-85729-667-2
912 _aZDB-2-SCS
999 _c105254
_d105254