Abstract
Multi-focus image fusion aims to combine a set of images that are captured from the same scene but with different focuses for producing another sharper image. To tackle the above challenge, a novel framework about multi-focus image fusion is proposed, which belongs to the fusion method based on transform domain. The regions of input image are divided to three categories: detail, plain and transition. Selecting the appropriate decision index and combining with the global and local information to achieve image fusion. This framework is flexible and generic and brings in fusion images with higher spatial resolution.
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References
Goshtasby, A.A., Nikolov, S.: Image fusion: adbances in the state of the art. Information Fusion 8(2), 114–118 (2008)
Tian, J., Chen, L., Ma, L., et al.: Multi-focus image fusion using a bilateral gradient-based sharpness criterion. Optics Communications 284, 80–87 (2011)
Li, S., Kwok, J.T., Wang, Y.: Combination of images with diverse focuses using the spatial frequency. Information Fusion 2, 169–176 (2001)
Huang, W., Jing, Z.: Evaluation of focus measures in multi-focus image fusion. Pattern Recognition Letters 28, 493–500 (2007, 2008)
Huang, W., Jing, Z.: Multi-focus image fusion using pulse coupled neural network. Pattern Recognition Letters 28, 1123–1132 (2007)
Li, H., Manjunath, B.S., Mitra, S.K.: Multisensor image fusion using the wavelet transform. Graphical Models and Image Processing 57, 235–245 (1995)
De, I., Chanda, B., Chattopadhyay, B.: Enhancing effective depth-of field by image fusion using mathematical morphology. Image and Vision Computing 24(12), 1278–1287 (2006)
Tian, J., Chen, L.: Adaptive multi-focus image fusion using a wavelet-based statistical sharpness measure 92, 2137–2146 (2012)
Nikolov, S.G., Lewis, J.J., O’Callaghan, R.J., et al.: Hybrid fused displays: between pixel- and regionbased image fusion. In: Proceedings of 7th International Conference on Information Fusion, Stockholm, Sweden, pp. 1072–1079 (June 2004)
Piella, G.: A general framework for multiresolution image fusion: from pixels to regions. Information Fusion 4(4), 259–280 (2003)
Luo, X., Wu, X.: New metric of image fusion based on region similarity. Optical Engineering 49(4), 047006-1–047006-13 (2010)
Thung, K.-H., Paramesran, R., et al.: Content-based image quality metric using similarity measure of moment vectors. Pattern Recognition 45, 2193–2204 (2012)
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© 2012 Springer-Verlag Berlin Heidelberg
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Luo, X., Wu, X., Zhang, Z. (2012). A Novel Framework about Multi-focus Image Fusion. In: Wang, F.L., Lei, J., Lau, R.W.H., Zhang, J. (eds) Multimedia and Signal Processing. CMSP 2012. Communications in Computer and Information Science, vol 346. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35286-7_5
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DOI: https://doi.org/10.1007/978-3-642-35286-7_5
Publisher Name: Springer, Berlin, Heidelberg
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