DSM generation from multiple digital aerial images in urban area

Yang Ming; Yingdan Wu

doi:10.1117/12.812570

3 November 2008 DSM generation from multiple digital aerial images in urban area

Yang Ming, Yingdan Wu

Proceedings Volume 7143, Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Geo-Simulation and Virtual GIS Environments; 714318 (2008) https://doi.org/10.1117/12.812570
Event: Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Geo-Simulation and Virtual GIS Environments, 2008, Guangzhou, China

Abstract

In this paper, we present a matching method for DSM generation from multiple images based on feature points, which introduce the coarse-to-fine strategy, geometrically constrained matching and relaxation technology, the matching is guided by the information in the object and make full use of the information in both image and object space. A match appearing in any pair has the chance to survive, and very dense disparity maps are obtained. Experiments have been performed and the height accuracy of the derived DSM is about 3 pixels.

Citation Download Citation

Yang Ming and Yingdan Wu "DSM generation from multiple digital aerial images in urban area", Proc. SPIE 7143, Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Geo-Simulation and Virtual GIS Environments, 714318 (3 November 2008); https://doi.org/10.1117/12.812570

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available