Super-resolution terrain map enhancement for navigation based on satellite imagery

Jeremy Straub

doi:10.1117/12.911942

23 January 2012 Super-resolution terrain map enhancement for navigation based on satellite imagery

Jeremy Straub

Author Affiliations +

Proceedings Volume 8301, Intelligent Robots and Computer Vision XXIX: Algorithms and Techniques; 83010J (2012) https://doi.org/10.1117/12.911942
Event: IS&T/SPIE Electronic Imaging, 2012, Burlingame, California, United States

Abstract

Super resolution techniques are commonly used to enhance images and video. The techniques have previously been applied to the enhancement of map data via enhancing aerial imagery. This paper proposes the use of super resolution techniques for enhancing topographic data directly. Specifically, a database-driven super resolution algorithm that is trained with domain-specific patterns is used to enhance topographic digital elevation model (DEM) data from NASA/NGIA SRTM. This enhancement process is evaluated using a elevation-difference evaluation technique where downscaled and enhanced DEM data is compared to the origional higher-resolution data. It is also evaluated with a threshold-based elevation difference metric and visually. The benefits that it might have for flight path planning for a UAV application are discussed. The challenges of using super resolution style techniques on non-visual data are also reviewed.

Citation Download Citation

Jeremy Straub "Super-resolution terrain map enhancement for navigation based on satellite imagery", Proc. SPIE 8301, Intelligent Robots and Computer Vision XXIX: Algorithms and Techniques, 83010J (23 January 2012); https://doi.org/10.1117/12.911942

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