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Adaptive image rational upscaling with local structure as constraints

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Abstract

In this paper, we develop a new interpolation fusion model, Adaptive Image Rational Upscaling (AIRU), based on classical rational interpolation. This model can synthetically consider the influence of the surrounding 12 pixels within the current interpolation cell. Considering the limitation of edge direction estimation of conventional edge detection methods, we introduce a new method to quantify the edge direction based on the Principal Component Edge (PCE). Adaptive weights for each triangular patch can be generated based on three coefficients: angle coefficient which can be estimated by PCE, variation coefficient and gray similarity coefficient. PCE can also be used to divide the image into non-smooth and smooth area. AIRU and conventional interpolation are used in these two areas respectively. Furthermore, the model parameter optimization can further improve the interpolation performance. Experimental results demonstrate that the proposed fusion model achieves competitive performance when compared with the state-of-the-arts.

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References

  1. Asuni N, Giachetti A (2008) Accuracy improvements and artifacts removal in edge based image interpolation. In: Proceedings of international conference on computer vision theory and applications, pp 58–65

  2. Bevilacqua M, Roumy A, Guillemot C, line M, Morel A (2012) Low-complexity single-image superresolution based on nonnegative neighbor embedding. In: Proceedings of the British machine vision conference, vol 135, p 110

  3. Cui CR, Ma J, Lian T, Chen ZM, Wang SQ (2015) Improving image annotation via ranking-oriented neighbor search and learning-based keyword propagation. J Assoc Inf Sci Technol 66:82–98

    Article  Google Scholar 

  4. Cui CR, Shen JL, Nie LQ, Hong RC, Ma J (2017) Augmented collaborative filtering for sparseness reduction in personalized POI recommendation. ACM Transactions on Intelligent Systems and Technology

  5. Dong WS, Zhang L, Lukac R (2013) Sparse representation based image interpolation with nonlocal autoregressive modeling. IEEE Trans Image Process 22:1382–1394

    Article  MathSciNet  Google Scholar 

  6. Duan Q, Djidjeli K, Price WG, Twizell EH (1999) The approximation properties of some rational cubic splines. Int J Comput 72:155–166

    Article  MathSciNet  Google Scholar 

  7. Duan Q, Zhang HL, Zhang YF (2006) Bounded property and point control of a bivariate rational interpolating surface. Comput Math Appl 52:975–984

    Article  MathSciNet  Google Scholar 

  8. Duan Q, Zhang YF, Twizell EH (2006) A bivariate rational interpolation and the properties. Appl Math Comput 179:190–199

    MathSciNet  MATH  Google Scholar 

  9. Edward A (2009) Interactive computer graphics: a top-down approach using OpenGL. Publishing House of Electronics Industry(PHEI), pp 64–75

  10. Giachetti A, Asuni N (2011) Real-time artifact-free image upscaling. IEEE Trans Image Process 20:2760–2768

    Article  MathSciNet  Google Scholar 

  11. Gonzalez RC, Woods RE (1992) Digital image processing. Addision-Wesley, Reading

    Google Scholar 

  12. Hou HS, Andrew HC (1978) Cubic splines for image interpolation and digital filtering. IEEE Trans Acoust Speech Signal Process 26:508–517

    Article  Google Scholar 

  13. Huang JB, Singh A, Ahuja N (2015) Single image super-resolution from transformed self-exemplars.. In: IEEE conference on computer vision and pattern recognition

  14. Hung KW, Siu WC (2012) Robust soft-decision interpolation using weighted least square. IEEE Trans Image Process 21:1061–1069

    Article  MathSciNet  Google Scholar 

  15. Key RG (1981) Cubic convolution interpolation for digital image processing. IEEE Trans Acoust Speech Signal Process 29:1153–1160

    Article  MathSciNet  Google Scholar 

  16. Li X, Orchard MT (2001) New edge-directed interpolation. IEEE Trans Image Process 10:1521–1527

    Article  Google Scholar 

  17. Liu YF, Zhang YF, Guo Q, Zhang CM (2014) Image interpolation based on weighted and blended rational fuction. ACCV Work Image Restor Ehance 9009:78–88

    Google Scholar 

  18. Shezaf N, Abramov-Segal H, Sutskover I, Ran BS (2000) Adaptive low complexity algorithm for imagezooming at fractional scaling ratio.. In: Proceeding of the 21st IEEE convention of the electrical and electronic engineers, pp 253–256

  19. Tomasi C, Manduchi R (1998) Bilateral filtering for gray and color images.. In: Sixth international conference on computer vision (IEEE Cat. No.98CH36271), pp 836–846

  20. Yao XX, Zhang YF, Bao FX, Liu YF, Zhang CM (2018) The blending interpolation algorithm based on image features. Multimedia Tools and Applications

  21. Zeyde R, Elad M, Protter M (2012) On single image scale-up using sparse-representations. In: Curves and surfaces, pp 711–730

    Chapter  Google Scholar 

  22. Zhang L, Wu X (2006) Image interpolation via directional filtering and data fusion. IEEE Trans Image Process 15:2226–2238

    Article  Google Scholar 

  23. Zhang XJ, Wu XL (2008) Image interpolation by adaptive 2-D autoregressive modeling and soft-decision estimation. IEEE Trans Image Process 17:887–896

    Article  MathSciNet  Google Scholar 

  24. Zhang X, Ma S, Zhang Y, Zhang L, Gao W (2009) Nonlocal edgedirected interpolation. In: Proceedings of advances in multimedia information processing, pp 1197–1207

    Chapter  Google Scholar 

  25. Zhang YF, Bao FX, Zhang CM (2011) Local shape control of a bivariate rational interpolating surface with mixing conditions.. In: Eighth international symposium on voronoi diagrams in science & engineering, pp 200–205

  26. Zhang YF, Bao FX, Zhang CM (2012) A weighted bivariate blending rational interpolation function and visualization control. J Comput Anal Appl 14:1303–1321

    MathSciNet  MATH  Google Scholar 

  27. Zhang CM, Zhang X, Li XM, Cheng FH (2013) Cubic surface fitting to image with edges as constraints.. In: IEEE international conference on image processing (ICIP), pp 1046–1050

  28. Zhang X, Liu Q, Li XM, Zhou YF, Zhang CM (2016) Non-local feature back-projection for image super-resolution. IET Image Process 10:398–408

    Article  Google Scholar 

  29. Zwart CM, Frakes DH (2013) Segment adaptive gradient angle interpolation. IEEE Trans Image Process 22:2960–2969

    Article  MathSciNet  Google Scholar 

Download references

Acknowledgments

This work is supported by the National Nature Foundation of China (61602277, 61572292, 61332015), NSFC Joint Fund with Zhejiang Integration of Informatization and Industrialization under Key Project(U1609218).

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Authors and Affiliations

  1. School of Computer Science and Technology, Shandong University, Jinan, 250100, China

    Yang Ning

  2. School of Software, Shandong University, Jinan, 250101, China

    Caiming Zhang

  3. Shandong Co-Innovation Center of Future Intelligent Computing, Yantai, 264025, China

    Caiming Zhang

  4. Shandong Province Key Lab of Digital Media Technology, Shandong University of Finance and Economics, Jinan, 250061, China

    Yunfeng Zhang & Caiming Zhang

  5. Department of Computer Science and Technology, Shandong University of Finance and Economics, Jinan, 250014, China

    Yunfeng Zhang

  6. Department of Computer Science and Engineering, University at Buffalo, New York, NY, 14260-1660, USA

    Yifang Liu

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  1. Yang Ning
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  2. Yifang Liu
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  3. Yunfeng Zhang
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  4. Caiming Zhang
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Correspondence to Caiming Zhang.

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Ning, Y., Liu, Y., Zhang, Y. et al. Adaptive image rational upscaling with local structure as constraints. Multimed Tools Appl 78, 6889–6911 (2019). https://doi.org/10.1007/s11042-018-6182-3

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  • DOI: https://doi.org/10.1007/s11042-018-6182-3

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