Super-resolution image reconstruction from UAS surveillance video through affine invariant interest point-based motion estimation

Qiang He; Richard R. Schultz; Yi Wang; Aldo Camargo; Florent Martel

doi:10.1117/12.764980

28 January 2008 Super-resolution image reconstruction from UAS surveillance video through affine invariant interest point-based motion estimation

Qiang He, Richard R. Schultz, Yi Wang, Aldo Camargo, Florent Martel

Author Affiliations +

Proceedings Volume 6808, Image Quality and System Performance V; 680814 (2008) https://doi.org/10.1117/12.764980
Event: Electronic Imaging, 2008, San Jose, California, United States

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.

Citation Download Citation

Qiang He, Richard R. Schultz, Yi Wang, Aldo Camargo, and Florent Martel "Super-resolution image reconstruction from UAS surveillance video through affine invariant interest point-based motion estimation", Proc. SPIE 6808, Image Quality and System Performance V, 680814 (28 January 2008); https://doi.org/10.1117/12.764980

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
11 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Super resolution

Video

Image registration

Image restoration

Video surveillance

Sensors

Motion estimation

Show All Keywords

Keywords/Phrases

Search In:

Publication Years