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Virtual Journal for Biomedical Optics

Virtual Journal for Biomedical Optics


  • Editors: Andrew Dunn and Anthony Durkin
  • Vol. 7, Iss. 11 — Oct. 31, 2012

Fast super-resolution using an adaptive Wiener filter with robustness to local motion

Russell C. Hardie and Kenneth J. Barnard  »View Author Affiliations

Optics Express, Vol. 20, Issue 19, pp. 21053-21073 (2012)

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We present a new adaptive Wiener filter (AWF) super-resolution (SR) algorithm that employs a global background motion model but is also robust to limited local motion. The AWF relies on registration to populate a common high resolution (HR) grid with samples from several frames. A weighted sum of local samples is then used to perform nonuniform interpolation and image restoration simultaneously. To achieve accurate subpixel registration, we employ a global background motion model with relatively few parameters that can be estimated accurately. However, local motion may be present that includes moving objects, motion parallax, or other deviations from the background motion model. In our proposed robust approach, pixels from frames other than the reference that are inconsistent with the background motion model are detected and excluded from populating the HR grid. Here we propose and compare several local motion detection algorithms. We also propose a modified multiscale background registration method that incorporates pixel selection at each scale to minimize the impact of local motion. We demonstrate the efficacy of the new robust SR methods using several datasets, including airborne infrared data with moving vehicles and a ground resolution pattern for objective resolution analysis.

© 2012 OSA

OCIS Codes
(100.6640) Image processing : Superresolution
(110.3080) Imaging systems : Infrared imaging
(280.4991) Remote sensing and sensors : Passive remote sensing

ToC Category:
Image Processing

Original Manuscript: July 12, 2012
Revised Manuscript: August 16, 2012
Manuscript Accepted: August 19, 2012
Published: August 29, 2012

Virtual Issues
Vol. 7, Iss. 11 Virtual Journal for Biomedical Optics

Russell C. Hardie and Kenneth J. Barnard, "Fast super-resolution using an adaptive Wiener filter with robustness to local motion," Opt. Express 20, 21053-21073 (2012)

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  1. S. C. Park, M. K. Park, and M. G. Kang, “Super-resolution image reconstruction: A technical overview,” IEEE Signal Processing Mag. 20, 21–36 (2003). [CrossRef]
  2. R. C. Hardie, R. R. Schultz, and K. E. Barner, “Super-resolution enhancement of digital video,” EURASIP J. Adv. Signal Process.2007, 19–19 (2007). [CrossRef]
  3. B. D. Lucas and T. Kanade, “An iterative image registration technique with an application to stereo vision,” in Proceedings of International Joint Conference on Artificial Intelligence (Vancouver, 1981), pp. 674–679.
  4. M. S. Alam, J. G. Bognar, R. C. Hardie, and B. J. Yasuda, “Infrared image registration using multiple translationally shifted aliased video frames,” IEEE Trans. Instrum. Meas.49 (2000). [CrossRef]
  5. M. Irani and S. Peleg, “Improving resolution by image registration,” CHIP: Graph. Models Image Process.53, 231–239 (1991). [CrossRef]
  6. R. C. Hardie, K. J. Barnard, J. G. Bognar, E. E. Armstrong, and E. A. Watson, “High-resolution image reconstruction from a sequence of rotated and translated frames and its application to an infrared imaging system,” Opt. Eng.37, 247–260 (1998). [CrossRef]
  7. R. C. Hardie, K. J. Barnard, and R. Ordonez, “Fast super-resolution with affine motion using an adaptive wiener filter and its application to airborne imaging,” Opt. Express19, 26208–26231 (2011). [CrossRef]
  8. M. D. Robinson and P. Milanfar, “Fundamental performance limits in image registration,” IEEE Trans. Image Processing13, 1185–1199 (2004). [CrossRef]
  9. M. D. Robinson and P. Milanfar, “Statistical performance analysis of super-resolution,” IEEE Trans. Image Processing15, 1413–1428 (2006). [CrossRef]
  10. R. C. Hardie, “Super-resolution using adaptive wiener filters,” in Super-Resolution Imaging, P. Milanfar, ed. (Taylor & Francis/CRC Press, 2010), pp. 35–61.
  11. R. C. Hardie, “A fast super-resolution algorithm using an adaptive wiener filter,” IEEE Trans. Image Processing16, 2953–2964 (2007). [CrossRef]
  12. B. Narayanan, R. C. Hardie, K. E. Barner, and M. Shao, “A computationally efficient super-resolution algorithm for video processing using partition filters,” IEEE Trans. Circuits Syst. Video Technol.17, 621–634 (2007). [CrossRef]
  13. M. Shao, K. E. Barner, and R. C. Hardie, “Partition-based interpolation for color filter array demosaicking and super-resolution reconstruction,” Opt. Eng.44, 107003–1–107003–14 (2005). [CrossRef]
  14. T. R. Tuinstra and R. C. Hardie, “High resolution image reconstruction from digital video by exploitation on non-global motion,” Opt. Eng.38 (1999). [CrossRef]
  15. M. Tanaka and M. Okutomi, “Towards robust reconstruction-based superresolution,” in Super-Resolution Imaging, P. Milanfar, ed. (Taylor & Francis/CRC Press, 2010), pp. 219–246.
  16. A. W. M. van Eekeren, K. Schutte, and L. J. van Vliet, “Multiframe super-resolution reconstruction of small moving objects,” IEEE Trans. Image Processing19, 2901–2912 (2010). [CrossRef]
  17. M. Kim, B. Ku, D. Chung, H. Shin, D. Han, and H. Ko, “Robust video super resolution algorithm using measurement validation method and scene change detection,” EURASIP J. Adv. Signal Process.2011, 1–12 (2011). 10.1186/1687-6180-2011-103. [CrossRef]
  18. Z. Zhang and R. Wang, “Robust image superresolution method to handle localized motion outliers,” Opt. Eng.48, 077005 (2009). [CrossRef]
  19. J. Dijk, A. W. M. van Eekeren, K. Schutte, D.-J. J. de Lange, and L. J. van Vliet, “Superresolution reconstruction for moving point target detection,” Opt. Eng.47, 096401 (2008). [CrossRef]
  20. N. A. El-Yamany and P. E. Papamichalis, “Robust color image superresolution: an adaptive m-estimation framework,” J. Image Video Process. 2008, 16:1–16:12 (2008).
  21. M. K. Park, M. G. Kang, and A. K. Katsaggelos, “Regularized high-resolution image reconstruction considering inaccurate motion information,” Opt. Eng.46, 117004 (2007). [CrossRef]
  22. Z. A. Ivanovski, L. Panovski, and L. J. Karam, “Robust super-resolution based on pixel-level selectivity,” Proc. SPIE6077, 607707 (2006). [CrossRef]
  23. S. Farsiu, D. Robinson, M. Elad, and P. Milanfar, “Fast and robust multi-frame super-resolution,” IEEE Trans. Image Processing13, 1327–1344 (2004). [CrossRef]
  24. S. Farsiu, S. Farsiu, S. Farsiu, D. Robinson, D. Robinson, M. Elad, M. Elad, P. Milanfar, and P. Milanfar, “Advances and challenges in super-resolution,” Int. J. Imag. Syst. Tech.14, 47–57 (2004). [CrossRef]
  25. F. O. Baxley, K. J. Barnard, R. C. Hardie, and M. A. Bicknell, “Flight test results of a rapid step-stare and microscan midwave infrared sensor concept for persistent surveillance,” in Proceedings of MSS Passive Sensors (Orlando, FL, 2010).
  26. R. D. Fiete, “Image quality and λ FN/ p for remote sensing systems,” Opt. Eng.38, 1229–1240 (1999). [CrossRef]
  27. R. Franzen, “Kodak lossless true color image suite,” http://r0k.us/graphics/kodak .
  28. P. Burt and E. Adelson, “The laplacian pyramid as a compact image code,” IEEE Trans. Communications31, 532–540 (1983). [CrossRef]
  29. A. C. Bovik, The Essential Guide to Video Processing (Academic Press, 2009), 2nd ed.
  30. S. Coles, An introduction to statistical modeling of extreme values, Springer Series in Statistics (Springer-Verlag, London, 2001).

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