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School of Electrical, Computer and Energy Engineering
M.S. Final Oral Defense
An Optimized Algorithm for Suppression of Atmospheric Distortion in Video
by
Abhishek Ashok Botadra
April 23, 2010
1:00 PM
GWC 208A
Committee:
Dr. David Frakes (chair)
Dr. Andreas Spanias
Dr. Martin Reisslein
Abstract
Atmospheric distortion is a naturally occurring phenomenon that affects a broad range of
optical sensors in both the visible light and infrared spectra. Because atmospheric
distortion reduces both effective spatial resolution and contrast in acquired images,
surveillance and tracking applications can be severely impacted. Fortunately, image
processing methods provide a solution to the atmospheric distortion problem.
Restoration algorithms can be applied to mitigate distortions and extend the functional
range of affected sensors. In this thesis, a signal processing algorithm is presented for the
suppression of atmospheric distortion in sensor video. The algorithm exploits the
properties that atmospheric distortion effects are spatially local and temporally quasiperiodic. The primary component of the algorithm is a modified control grid
interpolation, which is a hybrid motion estimation model that incorporates features of
both block-based and optical flow-based approaches. A dynamic motion vector field is
derived using the temporal history associated with a video sequence. That motion field is
then used to compensate for distortion. The proposed algorithm is mathematically
optimized based on specific characteristics of atmospheric distortion. Parallelization is
also integrated to make the algorithm suitable for hardware implementations and realtime multi-processor platforms. Performance is evaluated, in comparison to traditional
approaches, using a library of atmospherically distorted videos. Results indicate that
significant improvement in speed of execution is realized without sacrificing quality.