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Multi-kernel based adaptive interpolation for image super-resolution

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Abstract

This paper proposes a cost-effective and edge-directed image super-resolution scheme. Image super-resolution (image magnification) is an enthusiastic research area and is desired in a variety of applications. The basic idea of the proposed scheme is based on the concept of multi-kernel approach. Various stencils have been defined on the basis of geometrical regularities. This set of stencils is associated with the set of kernels. The value of a re-sampling pixel is obtained by calculating the weighted average of the pixels in the selected kernel. The time complexity of the proposed scheme is as low as that of classical linear interpolation techniques, but the visual quality is more appealing because of the edge-orientation property. The experimental results and analysis show that proposed scheme provides a good combination of visual quality and time complexity.

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Acknowledgments

This research is supported by the Industrial Strategic technology development program, 10041772, (The Development of an Adaptive Mixed-Reality Space based on Interactive Architecture) funded by the Ministry of Knowledge Economy (MKE, Korea).

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Authors and Affiliations

  1. College of Electronics and Information Engineering, Sejong University, Seoul, Korea

    Muhammad Sajjad, Naveed Ejaz & Sung Wook Baik

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  1. Muhammad Sajjad
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  2. Naveed Ejaz
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  3. Sung Wook Baik
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Correspondence to Sung Wook Baik.

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Sajjad, M., Ejaz, N. & Baik, S.W. Multi-kernel based adaptive interpolation for image super-resolution. Multimed Tools Appl 72, 2063–2085 (2014). https://doi.org/10.1007/s11042-012-1325-4

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  • DOI: https://doi.org/10.1007/s11042-012-1325-4

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