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Example Based Super Resolution Using Fuzzy Clustering and Neighbor Embedding

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Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 222))

Abstract

A fuzzy clustering based neighbor embedding technique for single image super resolution is presented in this paper. In this method, clustering information for low-resolution (LR) patches is learnt by Fuzzy K-Means clustering. Then by utilize the membership degree of each LR patch, a neighbor embedding technique is employed to estimate high resolution patches corresponding to LR patches. The experimental results show that the proposed method is very flexible and gives good results compared with other methods which use neighbor embedding.

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Correspondence to Keerthi A. S. Pillai .

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© 2013 Springer India

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Pillai, K.A.S., Wilscy, M. (2013). Example Based Super Resolution Using Fuzzy Clustering and Neighbor Embedding. In: S, M., Kumar, S. (eds) Proceedings of the Fourth International Conference on Signal and Image Processing 2012 (ICSIP 2012). Lecture Notes in Electrical Engineering, vol 222. Springer, India. https://doi.org/10.1007/978-81-322-1000-9_6

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  • DOI: https://doi.org/10.1007/978-81-322-1000-9_6

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  • Publisher Name: Springer, India

  • Print ISBN: 978-81-322-0999-7

  • Online ISBN: 978-81-322-1000-9

  • eBook Packages: EngineeringEngineering (R0)

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