Nothing Special   »   [go: up one dir, main page]
Skip to main content
Springer Nature Link
Log in

Efficient luma modification-based chroma down-sampling and novel luma down-sampling with adaptive interpolation

  • Original Paper
  • Published:
Signal, Image and Video Processing Aims and scope Submit manuscript

Abstract

In image/video processing, RGB to YUV transformation plays an important role in bit-rate reduction by a down-sampling of (U, V). Luma down-sampling is the trade-off between bit rate and PSNR, so it is transmitted as it is. In this paper first, we proposed luma down-sampling (LDS) on the server side. On the client side, luma up-sampling has been done by even distribution error (EDE) which introduced 5–7% PSNR lag. To improve PSNR, we proposed adaptive interpolation for luma (AIL) which improves up to 2% PSNR from EDE. LDS and AIL are suitable for low-cost applications. To improve PSNR, in conventional down-sampling format 4:2:2, 4:2:0, etc., we proposed bilinear-based efficient chroma up-sampling (BECU). BECU methods require eight neighbouring pixels where some pixels are up-sampled from the client side and some pixels are already down-sampled values at client side by BECU. This improves the PSNR and then bilinear interpolation-based chroma up-sampling.

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

Similar content being viewed by others

Data availability

Data sharing is not applicable to this article as no new data were created or analysed in this research.

References

  1. Wallace, G.K.: The JPEG still picture compression standard. IEEE Trans. Consum. Electron. 38(1), 43–59 (1991). https://doi.org/10.1109/30.125072

    Article  Google Scholar 

  2. Sullivan, G.J., Ohm, J.-R., Han, W.-J., Wiegand, T.: Overview of the high efficiency video coding (HEVC) standard. IEEE Trans. Circuits Syst. Video Technol. 22(12), 1649–1668 (2012)

    Article  Google Scholar 

  3. Parameter Values for High-Definition Television Systems for Production and International Programme Exchange, document ITU-R Rec. BT.709–5 (2002).

  4. Frajka, T., Zeger, K.: Downsampling dependent upsampling of images. Signal Process. Image Commun. 19(3), 257–265 (2004). https://doi.org/10.1016/j.image.2003.10.003

    Article  Google Scholar 

  5. Wu, X., Zhang, X., Wang, X.: Low bit-rate image compression via adaptive down-sampling and constrained least squares upconversion. IEEE Trans. Image Process. 18(3), 552–561 (2009). https://doi.org/10.1109/TIP.2008.2010638

    Article  ADS  MathSciNet  PubMed  Google Scholar 

  6. Zhang, Y., Zhao, D., Zhang, J., Xiong, R., Gao, W.: Interpolation dependent image downsampling. IEEE Trans. Image Process. 20(11), 3291–3296 (2011). https://doi.org/10.1109/TIP.2011.2158226

    Article  ADS  MathSciNet  PubMed  Google Scholar 

  7. Lin, C.-H., Chung, K.-L., Yu, C.-W.: Novel chroma subsampling strategy based on mathematical optimization for compressing mosaic videos with arbitrary RGB color filter arrays in H.264/AVC and HEVC. IEEE Trans. Circuits Syst. Video Technol. 26(9), 1722–1733 (2016). https://doi.org/10.1109/TCSVT.2015.2472118

    Article  Google Scholar 

  8. Shuyuan, Z., Chang, C., Ruiqin, X., Yuanfang, G., Bing, Z.: Efficient Chroma Sub-Sampling and Luma Modification for Color Image Compression. IEEE Trans Circuit Syst Video Technol (2019). https://doi.org/10.1109/TCSVT.2019.2895840

    Article  Google Scholar 

  9. Arun, P.V.: A comparative analysis of different DEM interpolation methods. Egyp J Remote Sens Space Sci 16(2), 133–139 (2013). https://doi.org/10.1016/j.ejrs.2013.09.001

    Article  MathSciNet  Google Scholar 

  10. Chung, K.L., Hsu, T.-C., Huang, C.-C.: Joint chroma subsampling and distortion-minimization-based luma modification for RGB color images with application. IEEE Trans. Image Process. 26(10), 4626–4638 (2017). https://doi.org/10.1109/TIP.2017.2719945

    Article  ADS  MathSciNet  PubMed  Google Scholar 

  11. Chung, K.L., Liu, T.Y., Cheng, J.S.: Novel and Optimal Luma Modification-Based Chroma Downsampling for Bayer Color Filter Array Images. IEEE Open J Circuit Syst 1(48–59), 2644–1225 (2020). https://doi.org/10.1109/OJCAS.2020.2996624

    Article  ADS  Google Scholar 

  12. Adaptive Basic Unit Layer Rate Control for JVT, document JVT-G012, ISO/IEC JTC1/SC29/WG11 and ITU-T SG16/Q.6, 7th Meeting, Pattaya, Thailand, (2003).

  13. Zhang, X., Wu, X.: Image interpolation by adaptive 2-D autoregressive modeling and soft-decision estimation. IEEE Trans. Image Process. 17(6), 887–896 (2008). https://doi.org/10.1109/TIP.2008.924279

    Article  ADS  MathSciNet  PubMed  Google Scholar 

  14. Bayer, B. E.: Color imaging array, U.S. Patent 3971 065 (1976).

  15. Li, X., Gunturk, B., Zhang, L.: Image demosaicing: A systematic survey. Imag. Vis. Commun. Image Process. 6822, 1–15 (2008). https://doi.org/10.1117/12.766768

    Article  Google Scholar 

  16. Zhang, L., Zhang, L., Mou, X., Zhang, D.: FSIM: A feature similarity index for image quality assessment. IEEE Trans. Image Process. 20(8), 2378–2386 (2011). https://doi.org/10.1109/TIP.2011.2109730

    Article  ADS  MathSciNet  PubMed  Google Scholar 

  17. Wang, S., Gu, K., Ma, S., Gao, W.: Joint chroma downsampling and upsampling for screen content image. IEEE Trans. Circuits Syst. Video Technol. 26(9), 1595–1609 (2016). https://doi.org/10.1109/TCSVT.2015.2461891

    Article  Google Scholar 

  18. Lin, T.-L., Yu, Y.-C., Jiang, K.-H., Liang, C.-F., Liaw, P.-S.: Novel chroma sampling methods for CFA video compression in AVC, HEVC and VVC, IEEE Trans. Circuits Syst. Video Technol. early access (2019). https://doi.org/10.1109/TCSVT.2019.2939280

    Article  Google Scholar 

  19. Kodak True Color Image Collection. [Online]. Available: http://r0k.us/graphics/kodak/

  20. Wang, Z., Bovik, A.C., Sheikh, H.R., Simoncelli, E.P.: Image quality assessment: From error visibility to structural similarity. IEEE Trans. Image Process. 13(4), 600–612 (2004). https://doi.org/10.1109/TIP.2003.819861

    Article  ADS  PubMed  Google Scholar 

  21. Wang, Z., Simoncelli, E.P., Bovik, A.C.: Multi-scale structural similarity for image quality assessment. Syst. Comput. (2003). https://doi.org/10.1109/ACSSC.2003.1292216

    Article  Google Scholar 

  22. Nef data file online http://www.luminescentphoto.com/nx2/nefs.html

  23. Chung, K.L., Lee, Y.-L., Chien, W.-C.: Effective gradient descent-based chroma subsampling method for Bayer CFA images in HEVC. IEEE Trans. Circuits Syst. Video Technol. 29(11), 3281–3290 (2019). https://doi.org/10.1109/TCSVT.2018.2879095

    Article  Google Scholar 

  24. IMAX dataset online https://www4.comp.polyu.edu.hk/~cslzhang/CDM_Dataset.htm

  25. Datta, B. N.: Numerical Linear Algebra and Applications, 1st ed. Philadelphia, PA, USA: Brooks/Cole, 315–324 (1995).

  26. Chen, H., Sun, M., Steinbach, E.: Compression of Bayer pattern video sequences using adjusted chroma subsampling. IEEE Trans. Circuits Syst. Video Technol. 19(12), 1891–1896 (2009). https://doi.org/10.1109/TCSVT.2009.2031370

    Article  Google Scholar 

Download references

Acknowledgements

The author would like to express his heartfelt gratitude to the supervisor for his guidance and unwavering support during this research for his guidance and support.

Funding

No financial support.

Author information

Authors and Affiliations

  1. Department of Electronics and Communication Engineering, PSN College of Engineering and Technology, Tirunelveli, Tamil Nadu, 627152, India

    A. Ahilan

  2. Department of Electronics and Communication Engineering, University College of Engineering, Tindivanam, Tamil Nadu, India

    B. Pradeep Khanth

  3. University College of Engineering Arni, Thiruvanamalai, Tamil Nadu, India

    R. Ezhilarasi

  4. Centre for Computational Imaging and Machine Vision, Department of Electronics and Communication Engineering, Sri Eshwar College of Engineering, Coimbatore, Tamil Nadu, 641202, India

    N. Muthukumaran

Authors
  1. A. Ahilan
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. B. Pradeep Khanth
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. R. Ezhilarasi
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. N. Muthukumaran
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

The authors confirm the contribution to the paper as follows: AA and BPK were involved in study conception and design; data collection was performed by RE; NM helped in analysis and interpretation of results; AA and BPK contributed to draft manuscript preparation; all authors reviewed the results and approved the final version of the manuscript.

Corresponding author

Correspondence to B. Pradeep Khanth.

Ethics declarations

Competing interests

This paper has no conflict of interest for publishing.

Ethical approval

My research guide reviewed and ethically approved this manuscript for publishing in this journal.

Human and Animal Rights

This article does not contain any studies with human or animal subjects performed by any of the authors.

Informed consent

I certify that I have explained the nature and purpose of this study to the above-named individual, and I have discussed the potential benefits of this study participation. The questions the individual had about this study have been answered, and we will always be available to address future questions.

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 (e.g. a society or other partner) 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

Ahilan, A., Pradeep Khanth, B., Ezhilarasi, R. et al. Efficient luma modification-based chroma down-sampling and novel luma down-sampling with adaptive interpolation. SIViP 18, 1415–1428 (2024). https://doi.org/10.1007/s11760-023-02814-6

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11760-023-02814-6

Keywords

Search

Navigation