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Proceedings Paper

Geometric super-resolution via log-polar FFT image registration and variable pixel linear reconstruction
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Paper Abstract

Various image de-aliasing techniques and algorithms have been developed to improve the resolution of pixel-limited imagery acquired by an optical system having an undersampled point spread function. These techniques are sometimes referred to as multi-frame or geometric super-resolution, and are valuable tools because they maximize the imaging utility of current and legacy focal plane array (FPA) technology. This is especially true for infrared FPAs which tend to have larger pixels as compared to visible sensors. Geometric super-resolution relies on knowledge of subpixel frame-toframe motion, which is used to assemble a set of low-resolution frames into one or more high-resolution (HR) frames. Log-polar FFT image registration provides a straightforward and relatively fast approach to estimate global affine motion, including translation, rotation, and uniform scale changes. This technique is also readily extended to provide subpixel translation estimates, and is explored for its potential combination with variable pixel linear reconstruction (VPLR) to apportion a sequence of LR frames onto a HR grid. The VPLR algorithm created for this work is described, and HR image reconstruction is demonstrated using calibrated 1/4 pixel microscan data. The HR image resulting from VPLR is also enhanced using Lucy-Richardson deconvolution to mitigate blurring effects due to the pixel spread function. To address non-stationary scenes, image warping, and variable lighting conditions, optical flow is also investigated for its potential to provide subpixel motion information. Initial results demonstrate that the particular optical flow technique studied is able to estimate shifts down to nearly 1/10th of a pixel, and possibly smaller. Algorithm performance is demonstrated and explored using laboratory data from visible cameras.

Paper Details

Date Published: 13 September 2011
PDF: 12 pages
Proc. SPIE 8165, Unconventional Imaging, Wavefront Sensing, and Adaptive Coded Aperture Imaging and Non-Imaging Sensor Systems, 81650O (13 September 2011); doi: 10.1117/12.894123
Show Author Affiliations
Peter N. Crabtree, Air Force Research Lab. (United States)
Jeremy Murray-Krezan, Air Force Research Lab. (United States)

Published in SPIE Proceedings Vol. 8165:
Unconventional Imaging, Wavefront Sensing, and Adaptive Coded Aperture Imaging and Non-Imaging Sensor Systems
Stanley Rogers; Jean J. Dolne; David P. Casasent; Thomas J. Karr; Victor L. Gamiz, Editor(s)

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