Region-based image fusion approach using iterative algorithm

Proceedings - 7th IEEE/ACIS International Conference on Computer and Information Science, IEEE/ACIS ICIS 2008, In conjunction with 2nd IEEE/ACIS Int. Workshop on e-Activity, IEEE/ACIS IWEA 2008

Volumn , Issue , 2008, Pages 202-207

  Zhang, Yingjie ^a   Ge, Liling ^b  

^a XI'AN JIAOTONG UNIVERSITY   (China)

^b XI'AN UNIVERSITY OF TECHNOLOGY   (China)

Author keywords

Energy function; Image fusion; Iterative strategy; Segmentation

Indexed keywords

COMMUNICATION; COMPUTER NETWORKS; CYBERNETICS; DATA FUSION; FUSION REACTIONS; GLOBAL OPTIMIZATION; IMAGE ENHANCEMENT; INFORMATION MANAGEMENT; INFORMATION SCIENCE; MATHEMATICAL PROGRAMMING; SIGNAL TO NOISE RATIO; STATISTICAL TESTS;

ENERGY FUNCTION; INTERNATIONAL CONFERENCES; ITERATIVE STRATEGY; SEGMENTATION; SOURCE IMAGING;

IMAGE FUSION;

EID: 51349088679     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICIS.2008.27     Document Type: Conference Paper

References (19)

1. L. Klein, Sensor and Data Fusion Concepts and Applications, Bellingham, WA: SPIE, 1999.
2. st Annual Conference on Information Sciences and Systems, 1997, pp. 168-173.
3. L. Rudin, S. Osher, and E. Fatemi, "Nonlinear total variation based noise removal algorithms", Physica, Vol. 60, 1992, pp. 259-268
4. P. Perona and J. Malik, "Scale-space and edge detection using anisotropic diffusion", IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.12, no.7, 1990, pp. 629-639.
5. T. F. Chan and L. A. Vese, "A level set algorithm for minimizing the Mumford-Shah functional in image processing", Proc. of the First IEEE Workshop on Variational and Level Set Methods in Computer Vision, 2001, pp. 161-168.
6. Y. J. Zhang and L. L. Ge, "A Hierarchical Segmentation Algorithm Based on Mumford and Shah Model", Proceedings of SNPD 2007, IEEE Computer Society, vol. 1, 2007, pp. 735-740.
7. T. F. Chan and L. A. Vese, "Active Contours without edges", IEEE Trans. Image Processing, vol.10, no.2, 2001, pp. 266-277.
8. G. Piella, "A region-based multi-resolution image fusion algorithm", ISIF Fusion conference, Annapolis, USA, 2002, pp. 1557-1564.
9. D. Mumford and J. Shah, "Optimal approximations by piecewise smooth functions and associated variational problems", Comm. Pure Appl. Math., vol.42, no.5, 1989, pp. 577-685.
10. V. S. Petrovic and C. S. Xydeas, "Sensor noise effects on signal-level image fusion performance", Information Fusion, no. 4, 2003, pp. 167-183.
11. J. Weickert, "A review of nonlinear diffusion filtering", Scale space theory in computer vision, LNCS 1252, Springer, Berlin, 1997, pp. 3-28.
12. Y. You, W. Xu, "A. Tannenbaum, M. Kaveh, Behavioral analysis of anisotropic diffusion in image processing", IEEE Trans. Image Process, vol.5, no.11, 1996, pp. 1539-1553.
13. B. Song and T. Chan, A fast algorithm for level set based optimization, UCLA, CAM-report 02-68, 2002.
14. S. Kim and H. Lim, "Method of background subtraction for medical image segmentation", Proceedings of the 3rd International Conference on Cybernetics and Information Technologies, Systems and Applications, 2006, pp. 87-91.
15. J. J. Lewis, R. J. O'Callaghan, S. G. Nikolov, D. R. Bull, and C. N. Canagarajah, "Region-based image fusion using complex wavelets", 7th International Conference on Information Fusion, Stockholm, Sweden, 28 June International Society of Information Fusion (ISIF), 2004, pp.555-562.
16. S. Mukhopadhyay and B. Chanda, "Fusion of 2D grey scale images using multi-scale morphology", Pattern Recognition, Vol. 34, 2001, pp. 1939-1949.
17. S. Osher and J. A. Sethian, "Fronts propagating with curvature dependent speed: algorithms based on Hamilton-Jacobi formulation", Journal of Computational Physics, vol.79, 1988, pp. 12-49.
18. T. A. Wilson, S. K. Rogers, and L. R. Myers, "Perceptual based hyperspectral image fusion using multiresolution analysis", Optical Engineering, vol.34, no.11, 1995, pp.3154-3164.
19. O. Rockinger, "Pixel-level fusion of image sequences using wavelet frames", Proceedings in Image Fusion and Shape Variability Techniques, Leeds, UK, 1996, pp. 149-154.11.