Multi-frame algorithms for the removal of atmospheric turbulence have proven effective under ideal conditions where the scene remains static; however, movement of the camera across a scene often introduces undesirable effects that degrade the quality of processed imagery to the point where it becomes unusable. This paper discusses the development of two solutions to this problem, each with different computational costs and levels of efficacy. We discuss a solution to this problem that uses robust registration methods to align a window of input images to each other and processes them to obtain a single improved frame, repeating the sequence of realignment and processing each time a new frame arrives. While this approach produces high quality results, the associated computational cost precludes real-time implementation, even on accelerated platforms. An alternative solution involves measuring scene movement through lightweight registration and quantification. Registration results are used to make a global determination of "safe" approaches to processing in order to avoid degraded results. This particular method is computationally inexpensive at the cost of efficacy. We discuss the performance of both of these modifications against the original, uncompensated algorithm in terms of computational cost and quality of output imagery. Additionally, we will briefly discuss future goals which aim to minimize additional computation while maximizing processing efficacy.

Date Published: 20 May 2011
PDF: 8 pages
Proc. SPIE 8060, Modeling and Simulation for Defense Systems and Applications VI, 806007 (20 May 2011); doi: 10.1117/12.884215

Published in SPIE Proceedings Vol. 8060:
Modeling and Simulation for Defense Systems and Applications VI
Eric J. Kelmelis, Editor(s)