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A Novel Statistical Fusion Rule for Image Fusion in Non Subsampled Contourlet Transform Domain

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Abstract

Image fusion provides an efficient way to merge the visual information from different images. A new method for image fusion is proposed based on Weighted Average Merging Method (WAMM) in the Non Subsampled Contourlet Transform domain. A performance analysis on various statistical fusion rules are also analysed. Analysis has been made on medical images, remote sensing images and multi focus images. Experimental results shows that the proposed method, WAMM obtained better results in NSCT domain than the wavelet domain as it preserves more edges and keeps the visual quality intact in the fused image.

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© 2012 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering

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Manu, V.T., Simon, P. (2012). A Novel Statistical Fusion Rule for Image Fusion in Non Subsampled Contourlet Transform Domain. In: Meghanathan, N., Chaki, N., Nagamalai, D. (eds) Advances in Computer Science and Information Technology. Computer Science and Information Technology. CCSIT 2012. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 86. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27317-9_38

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  • DOI: https://doi.org/10.1007/978-3-642-27317-9_38

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-27316-2

  • Online ISBN: 978-3-642-27317-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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