Multivariate statistical analysis of measures for assessing the quality of image fusion

International Journal of Image and Data Fusion

Volumn 1, Issue 1, 2010, Pages 47-66

  Li, Shuang ^a,b   Li, Zhilin ^b   Gong, Jianya ^a  

^a WUHAN UNIVERSITY   (China)

^b HONG KONG POLYTECHNIC UNIVERSITY   (Hong Kong)

Author keywords

Factor analysis; Hierarchical cluster analysis; Image fusion; Multivariate statistical analysis; Principal component; Quantitative quality assessment

Indexed keywords

EID: 77958071579     PISSN: 19479832     EISSN: 19479824     Source Type: Journal    
DOI: 10.1080/19479830903562009     Document Type: Article

References (38)

1. Aiazzi, B., et al., 2006. Information-theoretic assessment of fusion of multispectral and panchromatic images. Proceedings of the 9th international conference on information fusion, 10-13 July Florence, Italy, 1-5.
2. Aja-Fernandez, S., et al., 2006. Image quality assessment based on local variance. Proceedings of the 28th IEEE annual international conference on engineering in medicine and biology society, 30 August-3 September New York, USA, 4815-4818.
3. Almeida, J.A.S., et al., 2007. Improving hierarchical cluster analysis: a new method with outlier detection and automatic clustering. Chemometrics and Intelligent Laboratory Systems, 87 (2), 208-217.
4. Alparone, L., et al., 2004. A global quality measurement of pan-sharpened multispectral imagery. IEEE Geoscience and Remote Sensing Letters, 1 (4), 313-317.
5. Alparone, L., et al., 2006. A new method for MS + pan image fusion assessment without reference. IEEE international conference on geoscience and remote sensing symposium, 31 July-4 August Denver, USA, 3802-3805.
6. Alparone, L., et al., 2007. Comparison of pansharpening algorithms: outcome of the (2006) GRS-S data-fusion contest. IEEE Transactions on Geoscience and Remote Sensing, 45 (10), 3012-3021.
7. Angell, C., 2005. Fusion performance using a validation approach. Proceedings of the 8th international conference on information fusion, 25-28 July Waterfall Solutions, UK, 1170-1177.
8. Beaulieu, M., Foucher, S., and Gagnon, L., 2003. Multi-spectral image resolution refinement using stationary wavelet transform. IEEE International conference on geoscience and remote sensing symposium, 21-25 July Toulouse, France, 4032-4034.
9. Canga, E.F., et al., 2005. Characterisation of image fusion quality metrics for surveillance applications over bandlimited channels. Proceedings of the 8th international conference on information fusion, 25-28 July Waterfall Solutions, UK, 484-490.
10. Chen, Y. and Blum, R.S., 2005. Experimental tests of image fusion for night vision. Proceedings of the 8th international conference on information fusion, 25-28 July Waterfall Solutions, UK, 491-498.
11. Chen, K., et al., 2007. Multivariate statistical evaluation of trace elements in groundwater in a coastal area in Shenzhen, China. Environmental Pollution, 147 (3), 771-780.
12. Choi, M., et al., 2003. Biorthogonal wavelets-based Landsat 7 image fusion. Proceedings of the 24th Asian conference on remote sensing and the international symposium on remote sensing, 3-7 November Busan, Korea, 494-496.
13. Damera-Venkata, N., et al., 2000. Image quality assessment based on a degradation model. IEEE Transactions on Image Processing, 9 (4), 636-635.
14. Eskicioglu, A.M. and Fisher, P.S., 1995. Image quality measures and their performance. IEEE Transactions on Communications, 43 (12), 2959-2965.
15. Karathanassi, V., Kolokousis, P., and Ioannidou, S., 2007. A comparison study on fusion methods using evaluation indicators. International Journal of Remote Sensing, 28 (10), 2309-2341.
16. Kim, J.O. and Mueller, C.W., 1978. Introduction to factor analysis: what it is and how to do it. Quantitative applications in the social sciences series. Newbury Park, California: Sage University Press, 48-49.
17. Kite, T.D., Evans, B.L., and Bovik, A.C., 2000. Modeling and quality assessment of halftoning by error diffusion. IEEE Transactions on Image Processing, 9 (5), 909-922.
18. Lawley, D.N. and Maxwell, A.E., 1962. Factor analysis as a statistical method. Journal of the Royal Statistical Society, Series D (The Statistician), 12 (3), 209-229.
19. MacCallum, R., 1983. A comparison of factor analysis programs in SPSS, BMDP, and SAS. Psvchometrika, 48 (2), 223-231.
20. McKenna Jr, J.E., 2003. An enhanced cluster analysis program with bootstrap significance testing for ecological community analysis. Environmental Modelling and Software, 18 (3), 205-220.
21. Milligan, G.W., 1980. An examination of the effect of six types of error perturbation on fifteen clustering algorithms. Psychometrika, 45 (3), 325-342.
22. Parcharidis, I. and Kazi-Tani, L.M., (2000). Landsat TM and ERS data fusion: a statistical approach evaluation for four different methods. IEEE international conference on geoscience and remote sensing symposium, 24-28 July Honolulu, Hawaii, USA, 2120-2122.
23. Pohl, C. and Van Genderen, J.L., 1998. Multisensor image fusion in remote sensing: concepts, methods and applications. International Journal of Remote Sensing, 19 (5), 823-854.
24. Qu, G.H., Zhang, D.L., and Yan, P.F., 2002. Information measure for performance of image fusion. Electronics Letters, 38 (7), 313-315.
25. Ranchin, T. and Wald, L., 2000. Fusion of high spatial and spectral resolution images: the ARSIS concept and its implementation. Photogrammetric Engineering and Remote Sensing, 66 (1), 49-61.
26. Rodgers, J.L. and Nicewander, W.A., 1988. Thirteen ways to look at the correlation coefficient. The American Statistician, 42 (1), 59-66.
27. Sasikala, M. and Kumaravel, N., 2007. A comparative analysis of feature based image fusion methods. Information Technology Journal, 6 (8), 1224-1230.
28. Sheikh, H.R., Bovik, A.C., and de Veciana, G., 2005. An information fidelity criterion for image quality assessment using natural scene statistics. IEEE Transactions on Image Processing, 14 (12), 2117-2128.
29. Valet, L., Mauris, G., and Bolon, P., 2001. A statistical overview of recent literature in information fusion. IEEE Aerospace and Electronic Systems Magazine, 16 (3), 7-14.
30. Vijayaraj, V., O'Hara, C.G., and Younan, N.H., 2004. Quality analysis of pansharpened images. IEEE International conference on geoscience and remote sensing symposium, 20-24 September Alaska, USA, 85-88.
31. Wald, L., Ranchin, T., and Mangolini, M., 1997. Fusion of satellite images of different spatial resolutions: assessing the quality of resulting images. Photogrammetric Engineering and Remote Sensing, 63 (6), 691-699.
32. Wang, Z. and Bovik, A.C., 2002. A universal image quality index. IEEE Signal Processing Letters, 9 (3), 81-84.
33. Wang, Z. and Bovik, A.C., 2006. Modern image quality assessment. New York, USA: Morgan and Claypool.
34. Wang, Z., et al., 2004. Image quality assessment: from error visibility to structural similarity. IEEE Transaction on Image Processing, 13 (4), 600-612.
35. Wang, Z. and Simoncelli, E.P., 2005. Reduced-reference image quality assessment using a waveletdomain natural image statistic model. Proceedings of the Society of Photo-optical Instrumentation Engineers, Human Vision and Electronic Imaging X, 5666, 149-159.
36. Wold, S., Esbensen, K., and Geladi, P., 1987. Principle component analysis. Chemometrics and Intelligent Laboratory Systems, 2 (1), 37-52.
37. Xydeas, C. and Petrovic, V., 2000. Objective image fusion performance measure. Electronics Letters, 36 (4), 308-309.
38. Yang, X.H., et al., 2007. Fusion of multi-spectral and panchromatic images using fuzzy rule. Communications in Nonlinear Science and Numerical Simulation, 12 (7), 1334-1350.