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Proceedings Paper

Super-resolution image reconstruction from UAS surveillance video through affine invariant interest point-based motion estimation
Author(s): Qiang He; Richard R. Schultz; Yi Wang; Aldo Camargo; Florent Martel
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Paper Abstract

In traditional super-resolution methods, researchers generally assume that accurate subpixel image registration parameters are given a priori. In reality, accurate image registration on a subpixel grid is the single most critically important step for the accuracy of super-resolution image reconstruction. In this paper, we introduce affine invariant features to improve subpixel image registration, which considerably reduces the number of mismatched points and hence makes traditional image registration more efficient and more accurate for super-resolution video enhancement. Affine invariant interest points include those corners that are invariant to affine transformations, including scale, rotation, and translation. They are extracted from the second moment matrix through the integration and differentiation covariance matrices. Our tests are based on two sets of real video captured by a small Unmanned Aircraft System (UAS) aircraft, which is highly susceptible to vibration from even light winds. The experimental results from real UAS surveillance video show that affine invariant interest points are more robust to perspective distortion and present more accurate matching than traditional Harris/SIFT corners. In our experiments on real video, all matching affine invariant interest points are found correctly. In addition, for the same super-resolution problem, we can use many fewer affine invariant points than Harris/SIFT corners to obtain good super-resolution results.

Paper Details

Date Published: 28 January 2008
PDF: 11 pages
Proc. SPIE 6808, Image Quality and System Performance V, 680814 (28 January 2008); doi: 10.1117/12.764980
Show Author Affiliations
Qiang He, Mississippi Valley State Univ. (United States)
Richard R. Schultz, Univ. of North Dakota (United States)
Yi Wang, Univ. of North Dakota (United States)
Aldo Camargo, Univ. of North Dakota (United States)
Florent Martel, Univ. of North Dakota (United States)

Published in SPIE Proceedings Vol. 6808:
Image Quality and System Performance V
Susan P. Farnand; Frans Gaykema, Editor(s)

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