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A Fuzzy Lattice Approach to Automated Multimodal Image Fusion

by Biswajit Biswas, Kashinath Dey, Amlan Chakrabarti
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 45 - Number 20
Year of Publication: 2012
Authors: Biswajit Biswas, Kashinath Dey, Amlan Chakrabarti
10.5120/7030-9213

Biswajit Biswas, Kashinath Dey, Amlan Chakrabarti . A Fuzzy Lattice Approach to Automated Multimodal Image Fusion. International Journal of Computer Applications. 45, 20 ( May 2012), 1-7. DOI=10.5120/7030-9213

@article{ 10.5120/7030-9213,
author = { Biswajit Biswas, Kashinath Dey, Amlan Chakrabarti },
title = { A Fuzzy Lattice Approach to Automated Multimodal Image Fusion },
journal = { International Journal of Computer Applications },
issue_date = { May 2012 },
volume = { 45 },
number = { 20 },
month = { May },
year = { 2012 },
issn = { 0975-8887 },
pages = { 1-7 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume45/number20/7030-9213/ },
doi = { 10.5120/7030-9213 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:38:03.796987+05:30
%A Biswajit Biswas
%A Kashinath Dey
%A Amlan Chakrabarti
%T A Fuzzy Lattice Approach to Automated Multimodal Image Fusion
%J International Journal of Computer Applications
%@ 0975-8887
%V 45
%N 20
%P 1-7
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper presents a new technique for multimodal image fusion. Unlike most previous works on image fusion, this paper explores the use of fuzzy lattice theory in the fusion process. Our proposed image fusion algorithm involving infrared and visual images based on fuzzy lattice theory show better experimental result than the related research work. Finally the paper discusses several key topics for future research, including the applications of this technique to computer vision and other related fields

References
  1. David L. Hall and James Llinas. Handbook of multisensory data fusion, Electrical engineering and applied signal processing, ISBN 0-8493-2379-7.
  2. Dr Zhang Yin,Dr Andrew A Malcolm, Thermal and Visual Image Processing and Fusion, Machine Vision & Sensors Group, Automation Technology Division, 2000.
  3. G. Simone, A. Farina, F. C. Morabito, S. B. Serpico and L. Bruzzone, Image Fusion Techniques for Remote Sensing Applications, Information Fusion, Volume 3, Issue 1, Pages 3-15, March 2002.
  4. DAVID L. HALL, SENIOR MEMBER, IEEE, AND JAMES LLINAS. An Introduction to Multisensor Data Fusion, PROCEEDINGS OF THE IEEE, VOL. 85, NO. 1, JANUARY 1997.
  5. Jorge Nunez, Xavier Otazu, Octavi Fors and Albert Prades, Simultaneous Image Fusion And Reconstruction Using Wavelets; Applications to SPOT - LANDSAT Images, Vistas in Astronomy, Volume 41, Issue 3, Pages 351-357, 1997.
  6. L. Ding, A. Goshtasby and M. Satter, Volume Image Registration By Template Matching, Image and Vision Computing, Volume 19, Issue 12 Pages 821-832, 1 October 2001.
  7. L. J Chipman. , T. M. Orr, L. N. Graham, Wavelets and Image Fusion, Proceedings International Conference on Image Processing, vol. 3, Pages 248-251, 1995.
  8. M. A. Bowers, Optimization of Wavelets for Image Coding Using MATLAB, Dissertation (M. Eng. in Electronic & Communication Engineering) - University of Bath, 1997.
  9. Ravi K. Sharma and Misha Pavel, Multisensor Image Registration, in SID Digest, Society for Information Display, Vol. XXVIII, Pages 951-954, May 1997.
  10. Yaonan Wang, Multisensor Image Fusion: Concept, Method and Applications, Faculty of Electrical and Information Engineering, Hunan University, Changsha, 410082, China.
  11. Image fusion of visible and thermal images for fruit detection, D. M. Bulanon, T. F. Burks, V. Alchanatis,bio system engineering, Volume 103, Issue 1, May 2009, Pages 12-22.
  12. Pratt, W. K. , 1991, Digital Image Processing (New York: John Wiley).
  13. Buckley J J and Eslami E 2005 An Introduction to Fuzzy Logic and Fuzzy Sets, Physica-Verlag, A Springer-Verlag Company, Heidelberg.
  14. H. -J. Zimmermann (2001): Fuzzy Set Theory and its Applications, 4th ed. Kluwer Academic Publishers.
  15. Computational Gray-scale Mathematical Morphology on Lattices Real-Time Imaging, Volume, April 1995, Pages 69-85.
  16. G. Birkhoff, Lattice Theory, Vol. 25 (AMS, New York, 3rd ed. , 1973).
  17. L. A. Zadeh, Fuzzy sets, information, and Control 8 (1965) ,338-353.
  18. C. Tomasi R. Manduchi, Bilateral Filtering for Gray and Color Images, IEEE ICCV, 1998.
  19. J. P. Tremblay, R. Manohar, Discrete mathematical structures with application to computer science, Tata. McGraw-Hill Edition -1997,ISBN-0-07-065142-6.
  20. FUZZV RLGORITHMS With Applications to Image Processing and Pattern Recognition, Zheru Chi ,Hong Yan, Tuan Pham ,Advances in Fuzzy Systems Applications and Theory Vol. 10 , ISBN 9810226977
  21. The Eden Project Multi-Sensor Data Set, J. J. Lewis, S. G. Nikolov, A. Loza, T. Riley, D. Hickman, M. I. SmithTR-UoB-WS-Eden-Project-Data-Set 10th April 2006
Index Terms

Computer Science
Information Sciences

Keywords

Multimodal Fusion Infrared Image Normal Visual Image Fuzzy Lattice Image Registration Lattice

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