Spectral interpretation based on multisensor fusion for urban mapping

B. Csathó, T. Schenk, Suyoung Seo

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

8 Scopus citations

Abstract

This paper is concerned with fusing aerial imagery, LIDAR point clouds, and hyperspectral imagery for the purpose of automated urban mapping. Instead of performing traditional supervised and unsupervised classification of hyperspectral data we propose a region growing approach from seed pixels that originate from fusing LIDAR and aerial imagery. This requires a thorough alignment of all sensors involved - a problem that is solved with sensor invariant features. The common system is the geodetic reference frame in which the LIDAR points are computed. The alignment results in transformations from sensor space to object space and back, avoiding resampling the sensor data. After describing the major aspects, an example demonstrates the feasibility of the proposed fusion approach.

Original languageEnglish
Title of host publication2nd GRSS/ISPRS Joint Workshop on Remote Sensing and Data Fusion over Urban Areas, URBAN 2003
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages8-12
Number of pages5
ISBN (Electronic)0780377192, 9780780377196
DOIs
StatePublished - 2003
Event2nd GRSS/ISPRS Joint Workshop on Remote Sensing and Data Fusion over Urban Areas, URBAN 2003 - Berlin, Germany
Duration: 22 May 200323 May 2003

Publication series

Name2nd GRSS/ISPRS Joint Workshop on Remote Sensing and Data Fusion over Urban Areas, URBAN 2003

Conference

Conference2nd GRSS/ISPRS Joint Workshop on Remote Sensing and Data Fusion over Urban Areas, URBAN 2003
Country/TerritoryGermany
CityBerlin
Period22/05/0323/05/03

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