Local image registration by adaptive filtering. Caner, G., Tekalp, A. M., Sharma, G., & Heinzelman, W. IEEE TRANSACTIONS ON IMAGE PROCESSING, 15(10):3053-3065, OCT, 2006.
doi  abstract   bibtex   
We propose a new adaptive filtering framework for local image registration, which compensates for the effect of local distortions/displacements without explicitly estimating a distortion/displacement field. To this effect, we formulate local image registration as a two-dimensional (2-D) system identification problem with spatially varying system parameters. We utilize a 2-D adaptive filtering framework to identify the locally varying system parameters, where a new block adaptive filtering scheme is introduced. We discuss the conditions under which the adaptive filter coefficients conform to a local displacement vector at each pixel. Experimental results demonstrate that the proposed 2-D adaptive filtering framework is very successful in modeling and compensation of both local distortions, such as Stirmark attacks, and local motion, such as in the presence of a parallax field. In particular, we show that the proposed method can provide image registration to: a) enable reliable detection of watermarks following a Stirmark attack in nonblind detection scenarios, b) compensate for lens distortions, and c) align multiview images with nonparametric local motion.
@article{ ISI:000240776200016,
Author = {Caner, Gulcin and Tekalp, A. Murat and Sharma, Gaurav and Heinzelman,
   Wendi},
Title = {{Local image registration by adaptive filtering}},
Journal = {{IEEE TRANSACTIONS ON IMAGE PROCESSING}},
Year = {{2006}},
Volume = {{15}},
Number = {{10}},
Pages = {{3053-3065}},
Month = {{OCT}},
Abstract = {{We propose a new adaptive filtering framework for local image
   registration, which compensates for the effect of local
   distortions/displacements without explicitly estimating a
   distortion/displacement field. To this effect, we formulate local image
   registration as a two-dimensional (2-D) system identification problem
   with spatially varying system parameters. We utilize a 2-D adaptive
   filtering framework to identify the locally varying system parameters,
   where a new block adaptive filtering scheme is introduced. We discuss
   the conditions under which the adaptive filter coefficients conform to a
   local displacement vector at each pixel. Experimental results
   demonstrate that the proposed 2-D adaptive filtering framework is very
   successful in modeling and compensation of both local distortions, such
   as Stirmark attacks, and local motion, such as in the presence of a
   parallax field. In particular, we show that the proposed method can
   provide image registration to: a) enable reliable detection of
   watermarks following a Stirmark attack in nonblind detection scenarios,
   b) compensate for lens distortions, and c) align multiview images with
   nonparametric local motion.}},
DOI = {{10.1109/TIP.2006.877514}},
ISSN = {{1057-7149}},
ResearcherID-Numbers = {{Sharma, Gaurav/A-1154-2007}},
ORCID-Numbers = {{Sharma, Gaurav/0000-0001-9735-9519}},
Unique-ID = {{ISI:000240776200016}},
}
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