Visible and infrared video cameras are the most common imaging sensors used for video surveillance systems. Fusing concurrent visible and infrared imageries may further improve the overall detection and tracking performance of a video surveillance system. We performed image fusion using 13 pixel-based image fusion algorithms and examined their effects on the detection and tracking performance of a given target tracker. We identified five pyramid-based methods that produced significantly better performance, three of which also managed to achieve that with a relatively high efficiency.

Date Published: 17 May 2012
PDF: 10 pages
Proc. SPIE 8392, Signal Processing, Sensor Fusion, and Target Recognition XXI, 83920P (17 May 2012); doi: 10.1117/12.918373

Published in SPIE Proceedings Vol. 8392:
Signal Processing, Sensor Fusion, and Target Recognition XXI
Ivan Kadar, Editor(s)