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Proceedings Paper

Fast stereo matching under varying illumination
Author(s): Sarala Arunagiri; Adriana Contreras; Esthela Gallardo; Aritra DattaGupta; Patricia J. Teller; Joseph C. Deroba; Lam H. Nguyen
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Paper 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.

Paper Details

Date Published: 4 May 2012
PDF: 16 pages
Proc. SPIE 8361, Radar Sensor Technology XVI, 83611H (4 May 2012); doi: 10.1117/12.919335
Show Author Affiliations
Sarala Arunagiri, The Univ. of Texas at El Paso (United States)
Adriana Contreras, The Univ. of Texas at El Paso (United States)
Esthela Gallardo, The Univ. of Texas at El Paso (United States)
Aritra DattaGupta, The Univ. of Texas at El Paso (United States)
Patricia J. Teller, The Univ. of Texas at El Paso (United States)
Joseph C. Deroba, U.S. Army Intelligence and Information Warfare Directorate (United States)
Lam H. Nguyen, Army Research Lab (United States)


Published in SPIE Proceedings Vol. 8361:
Radar Sensor Technology XVI
Kenneth I. Ranney; Armin W. Doerry, Editor(s)

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