MULTIMODALITY AND MULTIRESOLUTION IMAGE FUSION

Paul M. de Zeeuw, Eric J. E. M. Pauwels, Jungong Han

Abstract

Standard multiresolution image fusion of multimodal images may yield an output image with artifacts due to the occurrence of opposite contrast in the input images. Equal but opposite contrast leads to noisy patches, instable with respect to slight changes in the input images. Unequal and opposite contrast leads to uncertainty of how to interpret the modality of the result. In this paper a biased fusion is proposed to remedy this, where the bias is towards one image, the so-called iconic image, in a preferred spectrum. A nonlinear fusion rule is proposed to prevent that the fused image reverses the local contrasts as seen in the iconic image. The rule involves saliency and a local match measure. The method is demonstrated by artificial and real-life examples.

References

  1. Burt, P. and Adelson, E. (1983). The laplacian pyramid as a compact image code. IEEE Transactions on Communications, 31(4):532-540.
  2. Burt, P. J. and Kolczynski, R. J. (1993). Enhanced image capture through fusion. In Proceedings Fourth International Conference on Computer Vision, pages 173- 182, Los Alamitos, California. IEEE Computer Society Press.
  3. Cvejic, N., Canagarajah, C. N., and Bull, D. R. (2006). Image fusion metric based on mutual information and tsallis entropy. Electronic Letters, 42(11):626-627.
  4. De Zeeuw, P. M. (2005). A multigrid approach to image processing. In Kimmel, R., Sochen, N., and Weickert, J., editors, Scale Space and PDE Methods in Computer Vision, volume 3459 of Lecture Notes in Computer Science, pages 396-407. Springer-Verlag, Berlin Heidelberg.
  5. De Zeeuw, P. M. (2007). The multigrid image transform. In Tai, X.-C., Lie, K. A., Chan, T. F., and Osher, S., editors, Image Processing Based on Partial Differential Equations, Mathematics and Visualization, pages 309 - 324. Springer Berlin Heidelberg.
  6. De Zeeuw, P. M., Piella, G., and Heijmans, H. J. A. M. (2004). A matlab toolbox for image fusion (matifus). CWI Report PNA-E0424, Centrum Wiskunde & Informatica, Amsterdam.
  7. Forster, B., van de Ville, D., Berent, J., Sage, D., and Unser, M. (2004). Complex wavelets for extended depth-offield: A new method for the fusion of multichannel microscopy images,. Microscopy Research and Technique, 65:33-42.
  8. Han, J., Pauwels, E., and de Zeeuw, P. (2011). Visible and infrared image registration employing line-based geometric analysis. MUSCLE International Workshop on Computational Intelligence for Multimedia Understanding, Pisa (Italy), Accepted for publication.
  9. Li, H., Manjunath, B. S., and Mitra, S. K. (1995). Multisensor image fusion using the wavelet transform. Graphical Models and Image Processing, 57(3):235-245.
  10. Liu, Z., Blasch, E., Xue, Z., Zhao, J., Laganière, R., and Wu, W. (2012). Objective assessment of multiresolution image fusion algorithms for context enhancement in night vision: a comparative study. IEEE Trans. on Pattern Analysis and Machine Intelligence, 34(1):94- 109.
  11. Mallat, S. (1989). A theory for multiresolution signal decomposition: the wavelet representation. IEEE Pattern Analysis and Machine Intelligence, 11(7):674- 693.
  12. Piella, G. (2003a). Adaptive Wavelets and their Applications to Image Fusion and Compression. PhD thesis, CWI & University of Amsterdam.
  13. Piella, G. (2003b). A general framework for multiresolution image fusion: from pixels to regions. Information Fusion, 9:259-280.
  14. Simoncelli, E. and Freeman, W. (1995). The steerable pyramid: a flexible architecture for multi-scale derivative computation. In Proceedings of the IEEE International Conference on Image Processing, pages 444- 447. IEEE Signal Processing Society.
  15. Zitov√°, B. and Flusser, J. (2003). Image registration methods: a survey. Image and Vision Computing, 21:977- 1000.
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Paper Citation


in Harvard Style

M. de Zeeuw P., J. E. M. Pauwels E. and Han J. (2012). MULTIMODALITY AND MULTIRESOLUTION IMAGE FUSION . In Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2012) ISBN 978-989-8565-03-7, pages 151-157. DOI: 10.5220/0003866501510157


in Bibtex Style

@conference{visapp12,
author={Paul M. de Zeeuw and Eric J. E. M. Pauwels and Jungong Han},
title={MULTIMODALITY AND MULTIRESOLUTION IMAGE FUSION},
booktitle={Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2012)},
year={2012},
pages={151-157},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003866501510157},
isbn={978-989-8565-03-7},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2012)
TI - MULTIMODALITY AND MULTIRESOLUTION IMAGE FUSION
SN - 978-989-8565-03-7
AU - M. de Zeeuw P.
AU - J. E. M. Pauwels E.
AU - Han J.
PY - 2012
SP - 151
EP - 157
DO - 10.5220/0003866501510157