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A new hybrid image enlargement method using singular value decomposition and cubic spline interpolation

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Abstract

In this research, a new image enlargement scheme is proposed which is based on a hybrid combination of singular value decomposition (SVD) and the cubic spline interpolation method. The proposed scheme uses interpolation on SVD feature matrices which transfer the detailed information of lower dimension image to the higher dimension image in an efficient manner. Initially, the low-resolution image is split into two feature matrices and a weight matrix using SVD. These feature matrices are used in the cubic spline interpolation to find the intensity of intermediate pixels of the enlarged image. The step length of the interpolation function is optimized by the maximization of signal to noise ratio. The feature matrices obtained after the optimized interpolation are employed in the reconstruction of the output image. The proposed methodology is also applied to reconstruct the compressed images by taking a few most dominating eigenvectors of the interpolated images. The presented scheme is compared with three standard interpolation techniques visually and using entropy, signal to noise ratio, peak signal to noise ratio, and root mean square error as the performance measures. The results of the proposed work show superior visual performance and better SVD features transfer in the enlarged images as compared to the other schemes.

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Acknowledgements

The authors are thankful to Eternal University for providing the necessary facilities.

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Authors and Affiliations

  1. Department of Mathematics, Eternal University, Baru Sahib, Himachal Pradesh, India

    Sandipan Gupta & Shivani Ranta

  2. Department of Electronics and Telecommunication Engineering, Eternal University, Baru Sahib, Himachal Pradesh, India

    Dileep Kumar Sharma

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  1. Sandipan Gupta
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  2. Dileep Kumar Sharma
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  3. Shivani Ranta
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Correspondence to Shivani Ranta.

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Gupta, S., Sharma, D.K. & Ranta, S. A new hybrid image enlargement method using singular value decomposition and cubic spline interpolation. Multimed Tools Appl 81, 4241–4254 (2022). https://doi.org/10.1007/s11042-021-11767-2

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  • DOI: https://doi.org/10.1007/s11042-021-11767-2

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