In-band sub-pixel registration of wavelet-encoded images from sparse coefficients View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2017-05-26

AUTHORS

Vildan Atalay Aydin, Hassan Foroosh

ABSTRACT

Sub-pixel registration is a crucial step for applications such as super-resolution in remote sensing, motion compensation in magnetic resonance imaging, and nondestructive testing in manufacturing, to name a few. Recently, these technologies have been trending towards wavelet-encoded imaging and sparse/compressive sensing. The former plays a crucial role in reducing imaging artifacts, while the latter significantly increases the acquisition speed. In view of these new emerging needs for applications of wavelet-encoded imaging, we propose a sub-pixel registration method that can achieve direct wavelet domain registration from a sparse set of coefficients. We make the following contributions: (i) We devise a method of decoupling scale, rotation, and translation parameters in the Haar wavelet domain, (ii) we derive explicit mathematical expressions that define in-band sub-pixel registration in terms of wavelet coefficients, (iii) using the derived expressions, we propose an approach to achieve in-band sub-pixel registration, avoiding back and forth transformations. (iv) Our solution remains highly accurate even when a sparse set of coefficients are used, which is due to localization of signals in a sparse set of wavelet coefficients. We demonstrate the accuracy of our method, and show that it outperforms the state of the art on simulated and real data, even when the data are sparse. More... »

PAGES

1527-1535

References to SciGraph publications

  • 2012-10-27. Entropy-based image registration method using the curvelet transform in SIGNAL, IMAGE AND VIDEO PROCESSING
  • 2006-12-01. A Frequency Domain Approach to Registration of Aliased Images with Application to Super-resolution in EURASIP JOURNAL ON ADVANCES IN SIGNAL PROCESSING
  • 1999. Wavelet-Based Image Coding: An Overview in APPLIED AND COMPUTATIONAL CONTROL, SIGNALS, AND CIRCUITS
  • 2010-08-27. Geometric image registration under arbitrarily-shaped locally variant illuminations in SIGNAL, IMAGE AND VIDEO PROCESSING
  • 1988-06. Direct methods for recovering motion in INTERNATIONAL JOURNAL OF COMPUTER VISION
  • 2008-10-21. A Robust hierarchical motion estimation algorithm in noisy image sequences in the bispectrum domain in SIGNAL, IMAGE AND VIDEO PROCESSING
  • 1997-09. Alignment by Maximization of Mutual Information in INTERNATIONAL JOURNAL OF COMPUTER VISION
  • 2011. The Linear Ordering Problem, Exact and Heuristic Methods in Combinatorial Optimization in NONE
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    http://scigraph.springernature.com/pub.10.1007/s11760-017-1116-5

    DOI

    http://dx.doi.org/10.1007/s11760-017-1116-5

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