Fast stereo matching under varying illumination

Sarala Arunagiri; Adriana Contreras; Esthela Gallardo; Aritra DattaGupta; Patricia J. Teller; Joseph C. Deroba; Lam H. Nguyen

doi:10.1117/12.919335

3 May 2012 Fast stereo matching under varying illumination

Sarala Arunagiri, Adriana Contreras, Esthela Gallardo, Aritra DattaGupta, Patricia J. Teller, Joseph C. Deroba, Lam H. Nguyen

Author Affiliations +

Proceedings Volume 8361, Radar Sensor Technology XVI; 83611H (2012) https://doi.org/10.1117/12.919335
Event: SPIE Defense, Security, and Sensing, 2012, Baltimore, Maryland, United States

Abstract

Stereo matching is a technique of finding the disparity map or correspondence points between two images acquired from different sensor positions; it is a core process in stereoscopy. Automatic stereo processing, which involves stereo matching, is an important process in many applications including vision-based obstacle avoidance for unmanned aerial vehicles (UAVs), extraction of weak targets in clutter, and automatic target detection. Due to its high computational complexity, stereo matching algorithms are one of the most heavily investigated topics in computer vision. Stereo image pairs captured under real conditions, in contrast to those captured under controlled conditions are expected to be different from each other in aspects such as scale, rotation, radiometric differences, and noise. These factors contribute to and enhance the level of difficulty of efficient and accurate stereo matching. In this paper we evaluate the effectiveness of cost functions based on Normalized Cross Correlation (NCC) and Zero mean Normalized Cross Correlation (ZNCC) on images containing speckle noise, differences in level of illumination, and both of these. This is achieved via experiments in which these cost functions are employed by a fast version of an existing modern algorithm, the graph-cut algorithm, to perform stereo matching on 24 image pairs. Stereo matching performance is evaluated in terms of execution time and the quality of the generated output measured in terms of two types of Root Mean Square (RMS) error of the disparity maps generated.

Citation Download Citation

Sarala Arunagiri, Adriana Contreras, Esthela Gallardo, Aritra DattaGupta, Patricia J. Teller, Joseph C. Deroba, and Lam H. Nguyen "Fast stereo matching under varying illumination", Proc. SPIE 8361, Radar Sensor Technology XVI, 83611H (3 May 2012); https://doi.org/10.1117/12.919335

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

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
16 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Speckle

Image segmentation

Image processing

Synthetic aperture radar

Target detection

Unmanned aerial vehicles

Computer vision technology

Show All Keywords

Keywords/Phrases

Search In:

Publication Years