Advertisement

Efficient implementation of a cubic-convolution based image scaling engine

  • Xiang Wang
  • Yong Ding
  • Ming-yu Liu
  • Xiao-lang Yan
Article

Abstract

In video applications, real-time image scaling techniques are often required. In this paper, an efficient implementation of a scaling engine based on 4×4 cubic convolution is proposed. The cubic convolution has a better performance than other traditional interpolation kernels and can also be realized on hardware. The engine is designed to perform arbitrary scaling ratios with an image resolution smaller than 2560×1920 pixels and can scale up or down, in horizontal or vertical direction. It is composed of four functional units and five line buffers, which makes it more competitive than conventional architectures. A strict fixed-point strategy is applied to minimize the quantization errors of hardware realization. Experimental results show that the engine provides a better image quality and a comparatively lower hardware cost than reference implementations.

Key words

Cubic-convolution Hardware implementation Interpolation Engine 

CLC number

TN79+TP752 

References

  1. Aho, E., Vanne, J., Hamalainen, T.D., Kuusilinna, K., 2007. Configurable implementation of parallel memory based real-time video downscaler. Microprocess. Microsyst., 31(5):283–292. [doi:10.1016/j.micpro.2006.09.003]CrossRefGoogle Scholar
  2. Arandiga, F., Donat, R., Mulet, P., 2003. Adaptive interpolation of images. Signal Process., 83(2):459–464. [doi:10.1016/S0165-1684(02)00445-0]MATHCrossRefGoogle Scholar
  3. Chen, P.Y., Lien, C.Y., Lu, C.P., 2009. VLSI implementation of an edge-oriented image scaling processor. IEEE Trans. VLSI Syst., 17(9):1275–1284. [doi:10.1109/TVLSI.2008.2003003]CrossRefGoogle Scholar
  4. Erup, L., Gardner, F.M., Harris, R.A., 1993. Interpolation in digital modems. II. Implementation and performance. IEEE Trans. Commun., 41(6):998–1008. [doi:10.1109/26.231921]CrossRefGoogle Scholar
  5. Farrow, C.W., 1988. A Continuously Variable Digital Delay Element. IEEE Int. Symp. on Circuits and Systems, 3:2641–2645. [doi:10.1109/ISCAS.1988.15483]Google Scholar
  6. Feng, T., Xie, W.L., Yang, L.X., 2001. An Architecture and Implementation of Image Scaling Conversion. 4th Int. Conf. on ASIC, p.409–410. [doi:10.1109/ICASIC.2001.982587]Google Scholar
  7. Gardner, F.M., 1993. Interpolation in digital modems. I. Fundamentals. IEEE Trans. Commun., 41(3):501–507. [doi: 10.1109/26.221081]MATHCrossRefGoogle Scholar
  8. Her, I., Yuan, C.T., 1994. Resampling on a pseudohexagonal grid. CVGIP: Graph. Models Image Process., 56(4):336–347. [doi:10.1006/cgip.1994.1030]CrossRefGoogle Scholar
  9. Hong, K.P., Paik, J.K., Kim, H.J., Lee, C.H., 1996. An edge-preserving image interpolation system for a digital camcorder. IEEE Trans. Consum. Electron., 42(3):279–284. [doi:10.1109/30.536121]CrossRefGoogle Scholar
  10. Hou, H., Andrews, H., 1978. Cubic splines for image interpolation and digital filtering. IEEE Trans. Acoust. Speech Signal Process., 26(6):508–517. [doi:10.1109/TASSP.1978.1163154]MATHCrossRefGoogle Scholar
  11. Keys, R., 1981. Cubic convolution interpolation for digital image processing. IEEE Trans. Acoust. Speech Signal Process., 29(6):1153–1160. [doi:10.1109/TASSP.1981.1163711]MathSciNetMATHCrossRefGoogle Scholar
  12. Kim, C.H., Seong, S.M., Lee, J.A., Kim, L.S., 2003. Winscale: an image-scaling algorithm using an area pixel model. IEEE Trans. Circ. Syst. Video Technol., 13(6):549–553. [doi:10.1109/TCSVT.2003.813431]CrossRefGoogle Scholar
  13. Lehmann, T., Sovakar, A., Schmitt, W., Repges, R., 1997. A comparison of similarity measures for digital subtraction radiography. Comput. Biol. Med., 27(2):151–167. [doi:10.1016/S0010-4825(97)83769-9]CrossRefGoogle Scholar
  14. Lehmann, T.M., Gonner, C., Spitzer, K., 1999. Survey: interpolation methods in medical image processing. IEEE Trans. Med. Imag., 18(11):1049–1075. [doi:10.1109/42.816070]CrossRefGoogle Scholar
  15. Li, X., Orchard, M.T., 2001. New edge-directed interpolation. IEEE Trans. Image Process., 10(10):1521–1527. [doi:10.1109/83.951537]CrossRefGoogle Scholar
  16. Lin, C.C., Sheu, M.H., Chiang, H.K., Liaw, C., Wu, Z.C., 2008. The Efficient VLSI Design of BI-CUBIC Convolution Interpolation for Digital Image Processing. IEEE Int. Symp. on Circuits and Systems, p.480–483. [doi:10.1109/ISCAS.2008.4541459]Google Scholar
  17. Lin, C.C., Sheu, M.H., Liaw, C., Chiang, H.K., 2010. Fast first-order polynomials convolution interpolation for realtime digital image reconstruction. IEEE Trans. Circ. Syst. Video Technol., 20(9):1260–1264. [doi:10.1109/TCSVT.2010.2057017]CrossRefGoogle Scholar
  18. Nuno-Maganda, M.A., Arias-Estrada, M.O., 2006. Real-Time FPGA-Based Architecture for Bicubic Interpolation: an Application for Digital Image Scaling. Int. Conf. on Reconfigurable Computing and FPGAs, p.1–8. [doi:10.1109/RECONFIG.2005.34]Google Scholar
  19. Parker, J.A., Kenyon, R.V., Troxel, D.E., 1983. Comparison of interpolating methods for image resampling. IEEE Trans. Med. Imag., 2(1):31–39. [doi:10.1109/TMI.1983.4307610]CrossRefGoogle Scholar
  20. Sheikh, H.R., Sabir, M.F., Bovik, A.C., 2006. A statistical evaluation of recent full reference image quality assessment algorithms. IEEE Trans. Image Process., 15(11):3440–3451. [doi:10.1109/TIP.2006.881959]CrossRefGoogle Scholar
  21. Sheikh, H.R., Wang, Z., Cormack, L., Bovik, A.C., 2010. LIVE Image Quality Assessment Database Release 2. Available from http://live.ece.utexas.edu/research/quality/subjective.htm [Accessed on Oct. 18, 2010].
  22. Shi, H.J., Ward, R., 2002. Canny Edge Based Image Expansion. IEEE Int. Symp. on Circuits and Systems, 1:785–788. [doi:10.1109/ISCAS.2002.1009958]Google Scholar
  23. Shi, J.Z., Reichenbach, S.E., 2006. Image interpolation by two-dimensional parametric cubic convolution. IEEE Trans. Image Process., 15(7):1857–1870. [doi:10.1109/TIP.2006.873429]CrossRefGoogle Scholar
  24. Wang, Z., Bovik, A.C., Sheikh, H.R., Simoncelli, E.P., 2004. Image quality assessment: from error visibility to structural similarity. IEEE Trans. Image Process., 13(4):600–612. [doi:10.1109/TIP.2003.819861]CrossRefGoogle Scholar

Copyright information

© Journal of Zhejiang University Science Editorial Office and Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Xiang Wang
    • 1
  • Yong Ding
    • 1
  • Ming-yu Liu
    • 1
  • Xiao-lang Yan
    • 1
  1. 1.Institute of VLSI DesignZhejiang UniversityHangzhouChina

Personalised recommendations