Main Article Content
Abstract
Details of principal component analysis and spatial frequency are presented. Two image fusion architectures are developed to fuse multi focused images and their performance is compared. In first architecture source images to be fused are considered as whole in the fusion process. In second architecture the source images to be fused are divided into blocks and then used in the fusion process. Overall SF shows slightly better performance. Block based image fusion scheme (second architecture) shows superior performance. This architecture is very simple and can be used in real time applications.
Keywords
Article Details
References
- Varsheny P.K., "Multisensor Data Fusion", Elec. Comm. Engg., Journal, Vol.9 No. 12, pp. 245-253, 1997.
- Lau Wai Leung., Bruce King and Vijay Nohora., "Comparison of Image Fusion Technique Using Entropy and INI", 22nd Asian Conference on Remote Sensing, Singapore, Nov.5-9, 2001.
- Gonzalo Pajares and Jesus Manuel de la Cruz., "A Wavelet-based Image Fusion Tutorial", Pattern Recognition, Vol. 37, pp. 1855-1872, 2004.
- Mallet, S.G., "A Theory for Multiresolution Signal Decomposition: The Wavelet Representation", IEEE Trans. Pattern Anal. Mach. Intel., Vol. 11, No.7, pp.674-693, 1989.
- Wang, H., Peng, J and Wu, W., "Fusion Algorithm for Multisensor Image based on Discrete Multiwavelet Transform", IEE Pro. Vis. Image Signal Process, Vol. 149, No. 5, 2002.
- Shutao Li., James T. Kwok and Yaonan Wang., Combination of Images with Diverse Focuses Using the Spatial Frequency", Information Fusion, Vol. 2, pp. 169-176, 2001.
- http://en.wikipedia.org/wiki/Principal_component s_analysis.
- Eskicioglu, A.M. and Fisher, P.S., "Image Quantity Measures and their Performance", IEEE Trans. Commun. Vol. 43, No. 12, pp.2959-2965, 1995.
- Naidu, V.P.S., Girija, G. and Raol, J.R., "Evaluation of Data Association and Fusion Algorithms for Tracking in the Presence of Measurement Loss", AIAA Conference on Navigation, Guidance and
- Control, Austin, USA, August 11-14, 2003.
- Gonzalo, R. Arce., "Nonlinear Signal Processing A Statistical Approach", Wiley-Interscience Inc., Publication, USA, 2005.
- Rick S. Blum and Zheng Liu., "Multi-Sensor Image Fusion and its Applications", CRC Press, Taylor and
- Francis Group, Boca Raton, 2006.
References
Varsheny P.K., "Multisensor Data Fusion", Elec. Comm. Engg., Journal, Vol.9 No. 12, pp. 245-253, 1997.
Lau Wai Leung., Bruce King and Vijay Nohora., "Comparison of Image Fusion Technique Using Entropy and INI", 22nd Asian Conference on Remote Sensing, Singapore, Nov.5-9, 2001.
Gonzalo Pajares and Jesus Manuel de la Cruz., "A Wavelet-based Image Fusion Tutorial", Pattern Recognition, Vol. 37, pp. 1855-1872, 2004.
Mallet, S.G., "A Theory for Multiresolution Signal Decomposition: The Wavelet Representation", IEEE Trans. Pattern Anal. Mach. Intel., Vol. 11, No.7, pp.674-693, 1989.
Wang, H., Peng, J and Wu, W., "Fusion Algorithm for Multisensor Image based on Discrete Multiwavelet Transform", IEE Pro. Vis. Image Signal Process, Vol. 149, No. 5, 2002.
Shutao Li., James T. Kwok and Yaonan Wang., Combination of Images with Diverse Focuses Using the Spatial Frequency", Information Fusion, Vol. 2, pp. 169-176, 2001.
http://en.wikipedia.org/wiki/Principal_component s_analysis.
Eskicioglu, A.M. and Fisher, P.S., "Image Quantity Measures and their Performance", IEEE Trans. Commun. Vol. 43, No. 12, pp.2959-2965, 1995.
Naidu, V.P.S., Girija, G. and Raol, J.R., "Evaluation of Data Association and Fusion Algorithms for Tracking in the Presence of Measurement Loss", AIAA Conference on Navigation, Guidance and
Control, Austin, USA, August 11-14, 2003.
Gonzalo, R. Arce., "Nonlinear Signal Processing A Statistical Approach", Wiley-Interscience Inc., Publication, USA, 2005.
Rick S. Blum and Zheng Liu., "Multi-Sensor Image Fusion and its Applications", CRC Press, Taylor and
Francis Group, Boca Raton, 2006.