Skip to main content
SpringerLink
Log in

Software-Based Video/Audio Processing for Cellular Phones

  • Published:
Telecommunication Systems Aims and scope Submit manuscript

Abstract

Nowadays, most cellular phones are used beyond voice communication. Although the processing power of cellular phones is sufficient for most data applications, it is difficult to play video and audio contents in software because of their computational complexity and lack of basic tools for multimedia processing, so software-based multimedia processing on cellular phones is a challenging issue. Several transcoding methods are introduced to address this issue, but they are mainly of the DCT-domain conversion. Hence, they are only applicable to high-end cellular phones. To develop a solution for low-end and mid-tier cellular phones, we begin this paper by analyzing the complexity of existing video standards to see if it is possible to play them on cellular phones by software. Next, various coding profiles as combinations of subalgorithms are studied, and we select a profile that adapts its complexity to the processing power of cellular phones. Also, an efficient dithering algorithm called out-of-order dithering is developed. We implement the profile with out-of-order dithering in an actual cellular phone software environment and present the performance results. The performance results show that software based video/audio processing is indeed possible on low-end cellular phones.

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

Similar content being viewed by others

References

  1. Y. Arai, T. Agui and M. Nakajima, A fast DCT-SQ scheme for images, Transactions of IEICE 71 (1988) 1095–1097.

    Google Scholar 

  2. ARM, http://www.arm.com.

  3. P.A.A. Assuncao and M. Ghanbari, Transcoding of MPEG-2 video in the frequency domain, in: Proc. of IEEE Internat. Conf. on Acoustics, Speech, and Signal Processing (ICASSP), Vol. 4 (April 1997) pp. 2633–2636.

  4. Coding of audio-visual objects, part 2: visual, ISO/IEC, 14496-2 (December 1999).

  5. R. Dugad and N. Ahuja, A fast scheme for downsampling and upsampling in the DCT domain, in: Proc. of IEEE Internat. Conf. on Image Processing (ICIP), Vol. 2 (October 1999) pp. 909–913.

  6. E. Feig and S. Winograd, Fast algorithms for the discrete cosine transform, IEEE Transactions on Signal Processing 40 (1992) 2174–2193.

    Google Scholar 

  7. B. Gordon, N. Ghaddha and T.H. Meng, Low-power multiplierless YUV to RGB converter bases on human vision perception, invited chapter, in: Low Power/Low Voltage Integrated Circuits and Systems, ed. E. Sanchez-Sinencio (IEEE Press, New York, 1994) pp. 408–417.

    Google Scholar 

  8. A. Graps, An introduction to wavelets, IEEE Computational Science and Engineering 2(2) (1995) 50–61.

    Google Scholar 

  9. R. Han, P. Bhagwat, R. LaMaire, T. Mummert, V. Perret and J. Rubas, Dynamic adaptation in an image transcoding proxy for mobile Web browsing, IEEE Personal Communications Magazine (1998) 8–17.

  10. J.-H. Jeong and C. Yoo, A server-centric streaming model, in: Proc. of NOSSDAV 2000 (June 2000) pp. 25–34.

  11. Y. Joo, Y. Choi, H. Shim, H.G. Lee, K. Kim and N. Chang, Energy exploration and reduction of SDRAM memory systems, in: Proc. of ACM Conf. on Design Automation, USA (2002) pp. 892–897.

  12. D. Legall, MPEG – A video compression standard for multimedia applications, Communications of the ACM 34(4) (1991) 46–48.

    Google Scholar 

  13. D.A. Lelewer and D.S. Hirschberg, Data Compression, ACM Computing (Springer, Heidelberg/New York, 1989).

    Google Scholar 

  14. C. Loeffler, A. Ligtenberg and C.S. Moschytz, Practical fast 1D DCT algotithm with eleven multiplications, in: Proc. of ICASSP (1989) pp. 988–991.

  15. N. Merhav and V. Bhaskaran, Fast algorithms for DCT domain image down sampling and for inverse motion compensation, IEEE Transactions on Circuits and Systems Video Technology 7(3) (1997) 468–476.

    Google Scholar 

  16. D.G. Morrison, M.E. Nilson and M. Ghabari, Reduction of the bit-rate of compressed video while in its coded form, in: Proc. of Internat. Packet Video Workshop, Portland, OR (September 1994) pp. D17.1–17.4.

  17. Mulcahy C., Image compression using the Haar wavelet transform, Spelman Science and Mathematics Journal 1(1) (1997) 22–31.

    Google Scholar 

  18. Qualcomm Corp., http://www.qualcomm.com.

  19. I.E.G. Richardson, H.264 and MPEG-4 Video Compression (Wiley, New York, 2003).

    Google Scholar 

  20. A. Said and W.A. Pearlman, A new fast and efficient image codec based on set partitioning in hierarchical trees, IEEE Transactions on Circuits and Systems for Video Technology 6 (June 1996) 243–250.

    Google Scholar 

  21. Samsung Electronics Co., http://www.sec.co.kr.

  22. T. Shanableh and M. Ghanbari, Heterogeneous video transcoding to lower spatio-temporal resolutions and different encoding formats, IEEE Transactions on Multimedia 2(2) (2000) 101–110.

    Google Scholar 

  23. J.M. Shapiro, Embedded image coding using zero trees of wavelet coefficients, IEEE Transactions on Signal Processing 41(12) (1993) 3445–3462.

    Google Scholar 

  24. SK Telecom, http://www.sktelecom.com.

  25. B. Sostawa, T. Dannemann and J. Speidel, DSP-based transcoding of digital video signals with MPEG-2 format, IEEE Transactions on Consumer Electronics 46(2) (2000) 358–362.

    Google Scholar 

  26. R. Talluri, Error-resilient video coding in the ISO MPEG-4 standard, IEEE Communication Magazine 36 (June 1998) 112–119.

    Google Scholar 

  27. R. Ulichney, A review of halftoning techniques, Proceedings of SPIE 3963 (2000) 378–391.

    Google Scholar 

  28. Video coding for low bit rate communication, ITU-T Recommendation H.263, version 1 (November 1995), version 2 (January 1998), version 3 (November 2000).

  29. G.K. Wallace, The JPEG still picture compression standard, IEEE Transactions on Computer Electronics 38(1) (1991) 18–34.

    Google Scholar 

  30. J. Wen, P. Meshkat and J. Villasenor, Structured trees for lossless coding of quantized wavelet coefficients, in: Proc. of Asilomar Conf. on Signals, Systems, and Computers (November 1996) pp. 3–6.

  31. J. Youn and M. Sun, Motion vector refinement for high performance transcoding, IEEE Transactions on Multimedia 1(1) (1999) 30–40.

    Google Scholar 

  32. Q. Yu and K.J. Parker, Quality issues in blue noise halftoning, Proceedings of SPIE 3300 (1998) 376–385.

    Google Scholar 

  33. W. Zhu, K. Yang and M. Beacken, CIF-to-QCIF video bitstream down-conversion in the DCT domain, Bell Labs Technical Journal 3(3) (1998) 21–29.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Korea University, Anam 5 Ga, SeongBuk-Gu, Seoul, Republic of Korea

    Jin-Hwan Jeong & Chuck Yoo

Authors
  1. Jin-Hwan Jeong
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Chuck Yoo
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jin-Hwan Jeong.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Jeong, JH., Yoo, C. Software-Based Video/Audio Processing for Cellular Phones. Telecommun Syst 28, 185–210 (2005). https://doi.org/10.1007/s11235-004-5016-y

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11235-004-5016-y

Keywords

Search

Navigation