Local Image Registration by Adaptive Filtering

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 ident...

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Bibliographic Details
Published in:IEEE transactions on image processing 2006-10, Vol.15 (10), p.3053-3065
Main Authors: Caner, G., Tekalp, A.M., Sharma, G., Heinzelman, W.
Format: Article
Language:English
Subjects:
Adaptive filtering
Adaptive filters
Algorithms
Applied sciences
Artificial Intelligence
Cameras
Compensation
Cryptography
Detection, estimation, filtering, equalization, prediction
Distortion
Estimating
Exact sciences and technology
Image Enhancement - methods
Image Interpretation, Computer-Assisted - methods
Image processing
Image registration
Information Storage and Retrieval - methods
Information, signal and communications theory
Layout
Lenses
local image registration
Mathematical models
Microprocessors
Motion detection
Motion estimation
nonparametric image registration
Optical distortion
Pattern Recognition, Automated - methods
Signal and communications theory
Signal processing
Signal, noise
stirmark recovery
Subtraction Technique
Telecommunications and information theory
Two dimensional displays
watermark synchronization
Watermarking
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Description
Summary: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
ISSN:1057-7149
1941-0042
DOI:10.1109/TIP.2006.877514