Skip to main content
SpringerLink
Log in

An effective bilinear interpolation-based iterative chroma subsampling method for color images

  • Published:
Multimedia Tools and Applications Aims and scope Submit manuscript

Abstract

Prior to encoding a color image, such as the RGB full-color image IRGB, the Bayer color filter array (CFA) image IBayer, or the digital time delay integration CFA image IDTDI, performing chroma subsampling on the converted chroma image is a necessary step. Previously, several chroma subsampling methods were developed for IRGB, IBayer, and IDTDI independently. In this paper, we propose an effective bilinear interpolation-based iterative chroma subsampling method for the considered three image types simultaneously, achieving better reconstructed images. Based on the considered three types of images collected from the Kodak, IMAX, and SCI (screen content images), the comprehensive experimental results demonstrated that under the versatile video coding (VVC) platform, our chroma subsampling method achieves the best quality and quality-bitrate tradeoff of the reconstructed color images when compared with the existing chroma subsampling methods.

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

Access this article

Log in via an institution

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

Notes

  1. Execution code of the modified version of the demosaicking method [13] for IDTDI, URL: ftp://140.118.175.164/DTDIdemosaicing.

  2. Determinant values of Hessian matrix of the block-distortion in (8), URL: ftp://140.118.175.164/adaptive/detHD.pdf.

References

  1. Allebach J, Wong PW (1996) Edge-directed interpolation. In: Proceedings of 3rd IEEE international conference on image processing. https://doi.org/10.1109/ICIP.1996.560768, vol 3, pp 707–710

  2. Babu C, Chandy DA, Karthigaikumar P (2020) Novel chroma subsampling patterns for wireless capsule endoscopy compression. Neural Comput & Applic 32(10):6353–6362

    Article  Google Scholar 

  3. Bayer BE (1976) Color imaging array. US Patent 3,971,065

  4. Bjøntegaard G (2001) Calculation of average psnr differences between rd-curves (vceg-m33). In: Document VCEG-m33, 13th ITU-t video coding experts group (VCEG) meeting, Austin, TX,USA, pp 2–4

  5. Bodenstorfer E, Fürtler J, Brodersen J, Mayer KJ, Eckel C, Gravogl K, Nachtnebel H (2007) High-speed line-scan camera with digital time delay integration. In: Real-Time Image Processing 2007, International Society for Optics and Photonics. https://doi.org/10.1117/12.704516, vol 6496, p 64960I

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

    Article  Google Scholar 

  7. Chung KL, Yang WJ, Chen CH, Liao HYM, Zeng SM (2011) Efficient chroma subsampling strategy for compressing digital time delay integration mosaic video sequences in h.264/AVC. Journal of Electronic Imaging 20(2):1–16. https://doi.org/10.1117/1.3586799

    Article  Google Scholar 

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

    Article  Google Scholar 

  9. Datta BN (1995) Numerical linear algebra and applications, 1st edn. Philadelphia PA, USA,Brooks/Cole

  10. Eastman Kodak Company (2014) Kodak dataset. https://www.math.purdue.edu/lucier/PHOTO_CD/BMP_IMAGES/

  11. ITU-R (2011) BT-601-5: Studio encoding parameters of digital television for standard 4:3 and wide-screen 16:9 aspect ratios. International Telecommunications Union

  12. ITU-T Video Coding Experts Group and the ISO/IEC Moving Picture Experts Group (2020) VTM-8.0. https://vcgit.hhi.fraunhofer.de/jvet/VVCSoftware_VTM

  13. Kiku D, Monno Y, Tanaka M, Okutomi M (2013) Residual interpolation for color image demosaicking. In: 2013 IEEE international conference on image processing, pp 2304–2308 https://doi.org/10.1109/ICIP.2013.6738475

  14. Li X, Orchard MT (2001) New edge-directed interpolation. IEEE Trans Image Process 10(10):1521–1527. https://doi.org/10.1109/83.951537

    Article  Google Scholar 

  15. Li X, Gunturk B, Zhang L (2008) Image demosaicing: A systematic survey. In: Visual communications and image processing 2008, International Society for Optics and Photonics. https://doi.org/10.1117/12.766768, vol 6822, p 68221J

  16. Lin CH, Chung KL, Yu CW (2016) 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. https://doi.org/10.1109/TCSVT.2015.2472118

    Article  Google Scholar 

  17. Lin TL, Yu YC, Jiang KH, Liang CF, Liaw PS (2020) Novel chroma sampling methods for CFA video compression in AVC, HEVC and VVC. IEEE Trans Circuits Syst Video Technol 30(9):3167–3180. https://doi.org/10.1109/TCSVT.2019.2939280

    Article  Google Scholar 

  18. Lu Y, Li S, Shen H (2011) Virtualized screen: a third element for cloud–mobile convergence. IEEE Multimedia Magazine 18(2):4–11. https://doi.org/10.1109/MMUL.2011.33

    Article  Google Scholar 

  19. Lukac R, Plataniotis KN (2005) Color filter arrays: design and performance analysis. IEEE Trans Consum Electron 51(4):1260–1267. https://doi.org/10.1109/TCE.2005.1561853

    Article  Google Scholar 

  20. Ni Z, Ma KK, Zeng H, Zhong B (2020) Color image demosaicing using progressive collaborative representation. IEEE Trans Image Process 29:4952–4964. https://doi.org/10.1109/TIP.2020.2975978

    Article  Google Scholar 

  21. Ridge J, Karczewicz M (2007) Joint Video Team (JVT) of ISO/IEC MPEG & ITU-T VCEG (ISO/IEC JTC1/SC29/WG11 and ITU-T SG16 Q. 6)

  22. SCI Image Database (2021) ftp://140.118.175.164/SCI26

  23. Tan DS, Chen WY, Hua KL (2018) DeepDemosaicking: Adaptive image demosaicking via multiple deep fully convolutional networks. IEEE Trans Image Process 27(5):2408–2419. https://doi.org/10.1109/TIP.2018.2803341

    Article  MathSciNet  Google Scholar 

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

    Article  Google Scholar 

  25. Wang Z, Bovik AC, Sheikh HR, Simoncelli EP (2004) Image quality assessment: from error visibility to structural similarity. IEEE Trans Image Process 13(4):600–612. https://doi.org/10.1109/TIP.2003.819861

    Article  Google Scholar 

  26. Yu YC, Jhang JW, Wei X, Tseng HW, Wen Y, Liu Z, Lin TL, Chen SL, Chiou YS, Lee HY (2017) Chroma upsampling for YCbCr 420 videos. In: 2017 IEEE International Conference on Consumer Electronics - Taiwan (ICCE-TW). https://doi.org/10.1109/ICCE-China.2017.7991046, pp 163–164

  27. Zhang L, Wu X, Buades A, Li X (2011a) Color demosaicking by local directional interpolation and nonlocal adaptive thresholding. Journal of Electronic Imaging 20(2):023016–1–023016–16. https://doi.org/10.1117/1.3600632

    Article  Google Scholar 

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

    Article  MathSciNet  Google Scholar 

  29. Zhang L, Wu X, Buades A, Li X (2014) IMAX dataset. http://www.comp.polyu.edu.hk/cslzhang/CDM_Dataset.htm

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

    Article  MathSciNet  Google Scholar 

Download references

Acknowledgments

This work was supported by the contracts MOST-107-2221-E-011-108-MY3 and MOST-108-2221-E-011-077-MY3 of the Ministry of Science and Technology, Taiwan. The authors appreciate the valuable comments of the three anonymous referees and the proofreading help of Ms. C. Harrington to improve the manuscript.

Author information

Authors and Affiliations

  1. Department of Computer Science and Information Engineering, National Taiwan University of Science and Technology, No. 43, Section 4, Keelung Road, Taipei, 10672, ROC, Taiwan

    Kuo-Liang Chung & Szu-Ni Chen

Authors
  1. Kuo-Liang Chung
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Szu-Ni Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Kuo-Liang Chung.

Additional information

Publisher’s note

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

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Chung, KL., Chen, SN. An effective bilinear interpolation-based iterative chroma subsampling method for color images. Multimed Tools Appl 81, 32191–32213 (2022). https://doi.org/10.1007/s11042-022-12743-0

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11042-022-12743-0

Keywords

Search

Navigation