Skip to main content
Springer Nature Link
Log in

An efficient bicubic interpolation implementation for real-time image processing using hybrid computing

  • Original Research Paper
  • Published:
Journal of Real-Time Image Processing Aims and scope Submit manuscript

Abstract

Bicubic interpolation is a classic algorithm in the real-time image processing systems, which can achieve good quality at a relatively low hardware cost, and is also the fundamental component of many other much more complex algorithms. However, the multiply-accumulate units (MAC) in the bicubic require massive resources in the hardware-based implementation, which limits the use of the bicubic algorithm. In this article, a hybrid architecture of fix-point and stochastic computing is proposed to reduce the hardware resource consumption by computing the low-weight bits ambiguously. The proposed architecture is tested on standard image sets to survey the performance and is implemented on Intel Cyclone V and Xilinx Virtex-II targets to verify the hardware consumption. The experimental results show that the proposed architecture achieves significant resource reduction and even higher image processing speed compared to the existing architectures with comparable performance.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12

Similar content being viewed by others

References

  1. Ren, S., Guo, K., Ma, J., Zhu, F., Hu, B., Zhou, H.: Realistic medical image super-resolution with pyramidal feature multi-distillation networks for intelligent healthcare systems. Neural Computing and Applications, 1–16 (2021)

  2. Meng, B., Wang, L., He, Z., Jeon, G., Dou, Q., Yang, X.: Gradient information distillation network for real-time single-image super-resolution. J. Real-Time Image Proc. 18(2), 333–344 (2021)

    Article  Google Scholar 

  3. Jeon, G., Kang, S., Lee, J.-K.: A robust fuzzy-bilateral filtering method and its application to video deinterlacing. J. Real-Time Image Proc. 11(1), 223–233 (2016)

    Article  Google Scholar 

  4. Liang, J., Cao, J., Sun, G., Zhang, K., Van Gool, L., Timofte, R.: Swinir: Image restoration using swin transformer. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 1833–1844 (2021)

  5. Hui, Z., Li, J., Gao, X., Wang, X.: Progressive perception-oriented network for single image super-resolution. Inf. Sci. 546, 769–786 (2021)

    Article  MathSciNet  Google Scholar 

  6. Dong, C., Loy, C.C., He, K., Tang, X.: Learning a deep convolutional network for image super-resolution. In: European Conference on Computer Vision, pp. 184–199 (2014). Springer

  7. Dong, C., Loy, C.C., He, K., Tang, X.: Image super-resolution using deep convolutional networks. IEEE Trans. Pattern Anal. Mach. Intell. 38(2), 295–307 (2015)

    Article  Google Scholar 

  8. Ledig, C., Theis, L., Huszár, F., Caballero, J., Cunningham, A., Acosta, A., Aitken, A., Tejani, A., Totz, J., Wang, Z.: Photo-realistic single image super-resolution using a generative adversarial network. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 4681–4690 (2017)

  9. Freedman, G., Fattal, R.: Image and video upscaling from local self-examples. ACM Transactions on Graphics (TOG) 30(2), 1–11 (2011)

    Article  Google Scholar 

  10. Chen, Z., Ma, Y., Wang, Z.: Hybrid stochastic-binary computing for low-latency and high-precision inference of cnns. Regular Papers, IEEE Transactions on Circuits and Systems I (2022)

  11. Boukhtache, S., Blaysat, B., Grediac, M., Berry, F.: Alternatives to bicubic interpolation considering fpga hardware resource consumption. IEEE Transactions on Very Large Scale Integration (VLSI) Systems 29(2), 247–258 (2020)

  12. Keys, R.: Cubic convolution interpolation for digital image processing. IEEE Trans. Acoust. Speech Signal Process. 29(6), 1153–1160 (1981)

    Article  MathSciNet  MATH  Google Scholar 

  13. Lin, C.-C., Sheu, M.-H., Chiang, H.-K., Liaw, C., Wu, Z.-C., Tsai, W.-K.: An efficient architecture of extended linear interpolation for image processing. J. Inf. Sci. Eng. 26(2), 631–648 (2010)

    MathSciNet  MATH  Google Scholar 

  14. Boukhtache, S., Blaysat, B., Grédiac, M., Berry, F.: Fpga-based architecture for bi-cubic interpolation: the best trade-off between precision and hardware resource consumption. J. Real-Time Image Proc. 18(3), 901–911 (2021)

    Article  Google Scholar 

  15. Khaledyan, D., Amirany, A., Jafari, K., Moaiyeri, M.H., Khuzani, A.Z., Mashhadi, N.: Low-cost implementation of bilinear and bicubic image interpolation for real-time image super-resolution. In: 2020 IEEE Global Humanitarian Technology Conference (GHTC), pp. 1–5 (2020). IEEE

  16. Zhang, Y., Li, Y., Zhen, J., Li, J., Xie, R.: The hardware realization of the bicubic interpolation enlargement algorithm based on fpga. In: 2010 Third International Symposium on Information Processing, pp. 277–281 (2010). IEEE

  17. Ahmed, K.J., Yuan, B., Lee, M.J.: High-accuracy stochastic computing-based fir filter design. In: 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 1140–1144 (2018). IEEE

  18. Wu, D., Li, J., Yin, R., Hsiao, H., Kim, Y., San Miguel, J.: Ugemm: Unary computing architecture for gemm applications. In: 2020 ACM/IEEE 47th Annual International Symposium on Computer Architecture (ISCA), pp. 377–390 (2020). IEEE

  19. Zhang, Y., Zhang, X., Song, J., Wang, Y., Huang, R., Wang, R.: Parallel convolutional neural network (cnn) accelerators based on stochastic computing. In: 2019 IEEE International Workshop on Signal Processing Systems (SiPS), pp. 19–24 (2019). IEEE

  20. Nuño-Maganda, M.A., Arias-Estrada, M.O.: Real-time fpga-based architecture for bicubic interpolation: an application for digital image scaling. In: 2005 International Conference on Reconfigurable Computing and FPGAs (ReConFig’05), p. 8 (2005). IEEE

Download references

Acknowledgements

This work is supported by National Natural Science Foundation of China (Nos. 62001277 and 62001276) and the Airborne Integration Project.

Author information

Authors and Affiliations

  1. National Key Laboratory of Science and Technology on Communications, University of Electronic Science and Technology of China, Chengdu, 611731, China

    Yubin Zhu, Yonghang Dai, Kaining Han & Jianhao Hu

  2. Department of Microelectronics and Communication Engineering, Chongqing University, Chongqing, 400044, China

    Junchao Wang

Authors
  1. Yubin Zhu
    View author publications

    You can also search for this author inPubMed Google Scholar

  2. Yonghang Dai
    View author publications

    You can also search for this author inPubMed Google Scholar

  3. Kaining Han
    View author publications

    You can also search for this author inPubMed Google Scholar

  4. Junchao Wang
    View author publications

    You can also search for this author inPubMed Google Scholar

  5. Jianhao Hu
    View author publications

    You can also search for this author inPubMed Google Scholar

Corresponding authors

Correspondence to Kaining Han or Junchao Wang.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhu, Y., Dai, Y., Han, K. et al. An efficient bicubic interpolation implementation for real-time image processing using hybrid computing. J Real-Time Image Proc 19, 1211–1223 (2022). https://doi.org/10.1007/s11554-022-01254-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11554-022-01254-8

Keywords