Abstract
Image Fusion is a technique which attempts to combine complimentary information from multiple images of the same scene so that the fused image is more suitable for computer processing tasks and human visual system. In this paper, a simple yet efficient real time image fusion algorithm is proposed considering human visual properties in spatial domain. The algorithm is computationally simple and implemented very easily in real-time applications. Experimental results highlights the expediency and suitability of the algorithm and efficiency is carried by the comparison made between proposed and existing algorithm.
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References
Hall, D.L., Llinas, J.: An Introduction to Multisensor Data Fusion. Proceedings of the IEEE 85(1), 6–23 (1997)
Xydeas, C. S., Petrovic, V.: Objective Pixel-level Image Fusion Performance Measure. In: Procedding of SPIE, Sensor Fusion: Architectures, Algorithms, and Applications IV, vol. 4051, pp. 89–98. Society of Photographic Instrumentation Engineers (2002)
Chavez, P.S., Kwarteng, A.Y.: Extracting spectral contrast in Landsat thematic mapper image data using selective principal component analysis. Photogrammetric Engineering and Remote Sensing 55, 339–348 (1989)
Burt, P.J., Kolczynski, R.J.: Enhanced image capture through fusion. In: Proceedings of International Conference on Computer Vision, Berlin, Germany, pp. 173–182. IEEE Press, Los Alamitos (1993)
Li, H., Manjunath, B.S., Mitra, S.K.: Multisensor image fusion using the wavelet transform. Graph Models Image Processing 57(3), 235–245 (1995)
Qu, G., Zhang, D., Yan, P.: Medical Image Fusion by Wavelet Transform Modulus Maxima. Optics Express 9, 184–190 (2001)
Levicky, D., Foris, P.: Human visual system models in digital watermarking. Radioengineering 13(4), 38–43 (2004)
Voloshynovskiy, S., Herrigel, A., Baumgartner, N., Pun, T.: A stochastic apporach to content adaptive digital image watermarking. In: Pfitzmann, A. (ed.) IH 1999. LNCS, vol. 1768, pp. 211–236. Springer, Heidelberg (2000)
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Bhatnagar, G., Wu, Q.M.J., Raman, B. (2010). Real Time Human Visual System Based Framework for Image Fusion. In: Elmoataz, A., Lezoray, O., Nouboud, F., Mammass, D., Meunier, J. (eds) Image and Signal Processing. ICISP 2010. Lecture Notes in Computer Science, vol 6134. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13681-8_9
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DOI: https://doi.org/10.1007/978-3-642-13681-8_9
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