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Image Interpolation Based on Weighted and Blended Rational Function

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Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 9009))

Abstract

Conventional linear interpolation methods produce interpolated images with blurred edges, while edge directed interpolation methods make enlarged images with good quality edges but with details distortion for some cases. An adaptive rational-based algorithm for the interpolation of digital images with arbitrary scaling factors is proposed. In order to remove artifacts, we construct a new interpolation model with weight and blend, which are used for preserving the clear edge and detail. The proposed model is blended by basic rational interpolation model and three rotated rational models. The weight coefficients are determined by the edge information from different scale based on point sampling. Experimental results show that the proposed method produces images with high objective quality assessment value and good visual quality.

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Notes

  1. 1.

    The source code of the proposed method is opened, please request the first author.

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Acknowledgement

This work was partially supported by Projects of International Cooperation and Exchanges NSFC (61020106001), National Natural Science Foundation of China under Grant 61373080, Grant 61202150, Grant 61373078.

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Correspondence to Yunfeng Zhang .

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© 2015 Springer International Publishing Switzerland

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Liu, Y., Zhang, Y., Guo, Q., Zhang, C. (2015). Image Interpolation Based on Weighted and Blended Rational Function. In: Jawahar, C., Shan, S. (eds) Computer Vision - ACCV 2014 Workshops. ACCV 2014. Lecture Notes in Computer Science(), vol 9009. Springer, Cham. https://doi.org/10.1007/978-3-319-16631-5_6

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  • DOI: https://doi.org/10.1007/978-3-319-16631-5_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-16630-8

  • Online ISBN: 978-3-319-16631-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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