Nothing Special   »   [go: up one dir, main page]

Skip to main content
Log in

Super-resolution with selective filter based on adaptive window and variable macro-block size

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

Abstract

Super-resolution (SR) covers a set of techniques whose objective is to improve the spatial resolution of a video sequence or a single frame. In this scope, fusion SR techniques obtain high-resolution (HR) frames taking as a reference several low-resolution (LR) frames contained in a video sequence. This paper is based on a selective filter to decide the best LR frames to be used in the super-resolution process. Additionally, each frame division into macro-blocks (MBs) is analyzed both in a fixed block size approach, which decides which MBs should be used in the process, and in a variable block size approach with an adaptive MB size, which has been developed to set an appropriate frame division into MBs with variable size. These contributions not only improve the quality of video sequences, but also reduce the computational cost of a baseline SR algorithm, avoiding the incorporation of non-correlated data. Furthermore, this paper explains the way in which the enhanced algorithm proposed in it outperforms the quality of typical SR applications, such as underwater imagery, surveillance video, or remote sensing. The results are provided in a test environment to objectively compare the image quality enhancement obtained by bilinear interpolation, by the baseline SR algorithm, and by the proposed methods, thus presenting a quantitative comparison based on peak signal-to-noise ratio (PSNR) and Structural SIMilarity (SSIM) index parameters. The comparison has also been extended to other relevant proposals of the state of the art. The proposed algorithm significantly speeds up the previous ones, allowing real-time execution under certain conditions.

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

Access this article

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.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Fig. 17
Fig. 18
Fig. 19
Fig. 20
Fig. 21
Fig. 22

Similar content being viewed by others

References

  1. Yang, J., Huang, T.: Image Super-Resolution: Historical Overview and Future Challenges. In: Imaging, Super-Resolution (ed.) Boca Ratón, pp. 1–23. CRC Press, USA (2010)

    Google Scholar 

  2. Quevedo, Eduardo, Sánchez, Luis, Callicó, Gustavo M., Tobajas, Félix, de la Cruz, Jesús, Sarmiento, Roberto: Selective filter with adaptive size macro-block for super-resolution applications, IEEE International Symposium on Consumer Electronics (ISCE), pp. 101–102. Hsinchu, Taiwan (2013)

    Google Scholar 

  3. Núñez, A.: Advances in video coding for hand-held device implementation in networked electronic media. J. Real Time Image Process. 1(1), 9–23 (2006)

    Article  Google Scholar 

  4. de Fontes, F.P.X., Barroso, G.A., Coupé, P., Hellier, P.: Real time ultrasound image denoising. J. Real Time Image Process. 6(1), 15–22 (2010)

    Article  Google Scholar 

  5. Sarfraz, M.S., Shahzad, A., Elahi, M.A., Fraz, M., Zafar, I., Edirisinghe, E.A.: Real-time automatic license plate recognition for CCTV forensic applications. J. Real Time Image Process. 8(3), 285–295 (2011)

  6. Bowen, O., Bouganis, C.-S.: Real-time image super resolution using an FPGA. In: International Conference on Field Programmable Logic and Applications, pp. 89–94. Heidelberg, Germany (2008)

  7. Zomet, A., Rav-Acha, A., Peleg, S.: Robust super-resolution. In: Proceedings on computer Vision and Pattern Recognition, vol. 1, pp. I-645–I-650 (2001)

  8. Anagun, Y., Seke, E.: Super resolution using variable size block-matching motion estimation with rotation. In: Proceedings of the International Symposium on Innovations in Intelligent Systems and Applications, pp. 1–5. Trabzon, Turkey (2012)

  9. Callicó, G.M., Peset Llopis, R., Núñez, A., Sethuraman, R., de Beeck, MO.: A Low-Cost Implementation of Super-Resolution based on a Video Encoder. In: 28th Annual Conference of the IEEE Industrial Electronics Society IECON, vol. 2, pp. 1439–1444. Seville, Spain (2002)

  10. Heng, Su, Tang, Liang, Ying, Wu, Tretter, Daniel, Zhou, Jie: Spatially adaptive block-based Super-Resolution. IEEE Trans. Image Process. 21(3), 1031–1045 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  11. Anbarjafari, G., Demirel, H.: Image Super Resolution Based on Interpolation of Wavelet Domain High Frequency Subbands and the Spatial Domain Input Image. Electron. Telecommun. Res. Inst. J. 32(3), (2010)

  12. Jeong, S.C., Song, B.C.: Fast Super-Resolution Algorithm Based on Dictionary Size Reduction Using k-Means Clustering. Electron. Telecommun. Res. Inst. J. 32(4) (2010)

  13. Chen, Y., Li, W., Xia, M., Li, Q., Yang, K.: Super-resolution reconstruction for underwater imaging. Opt. Appl. XLI(4) (2011)

  14. Sheikh, H.R., Bovik, A.C.: Image information and visual quality. IEEE Trans. Image Process. 15(2), 430–444 (2006)

    Article  Google Scholar 

  15. Papoulis, A.: A new algorithm in spectral analysis and band-limited extrapolation. IEEE Trans. Circuits Syst. 22(9), 735–742 (1975)

    Article  MathSciNet  Google Scholar 

  16. Gerchberg, R.W.: Super-resolution through error energy reduction. Opt. Acta Int. J. Opt. 21(9), (1974)

  17. Li, J.J., Li, Q., Wang, D.:, Super-resolution reconstruction and enhancement for underwater video image. In: China National Knowledge Infrastructure (2011)

  18. Firoozfam, P.: Multi-Camera imaging for 3-D mapping and positioning; stereo and panoramic conical views, Ph.D. Thesis (2004)

  19. Wang, Zhou, Bovik, Alan C., Sheikh, Hamid R., Simoncelli, Eero P.: Image quality assessment: from error visibility to structural similarity. IEEE Trans. Imaging Process. 13(4) 600–612 (2004)

    Article  Google Scholar 

  20. Callicó, G.M., López, S., Sosa, O., López, J.F., Sarmiento, R.: Analysis of fast block matching motion estimation algorithms for video super-resolution. IEEE Trans. Consum. Electron. 54(3) 1430–1438 (2008)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to E. Quevedo.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Quevedo, E., Sánchez, L., M. Callicó, G. et al. Super-resolution with selective filter based on adaptive window and variable macro-block size. J Real-Time Image Proc 15, 389–406 (2018). https://doi.org/10.1007/s11554-015-0489-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11554-015-0489-3

Keywords

Navigation