한국항행학회논문지 (Journal of Advanced Navigation Technology)

  • 제19권6호
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  • Pages.614-622
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  • 2015
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  • 1226-9026(pISSN)
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  • 2288-842X(eISSN)
한국항행학회 (The Korean Navigation Institute)
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2진 MQ 산술부호기의 성능 개선

Performance Improvement of Binary MQ Arithmetic Coder

  • 고형화 (광운대학교 전자통신공학과) ;
  • 서석용 (경민대학교 정보통신과)
  • Ko, Hyung Hwa (Department of Electronics and Communication Engineering, Kwangwoon University) ;
  • Seo, Seok Yong (Department of Information & Communication, Kyungmin College)
  • 투고 : 2015.11.19
  • 심사 : 2015.12.07
  • 발행 : 2015.12.30
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초록

2진(binary) MQ 산술부호화는 최근 들어 멀티미디어 압축 표준시스템에 기본 엔트로피 방식으로 사용되고 있다. MQ 산술부호기는 JBIG2와 JPEG2000에 적용되면서 압축성능을 인정받기 시작했다. 최근에 차세대 동영상 부호화 표준인 HEVC (high efficiency video coding)에는 산술부호화가 단일 엔트로피부호화로 채택되면서 그 중요성이 커지고 있다. 기존의 2진 MQ 산술부호기는 RANGE(구간)을 분할하는 과정에서 곱셈을 없애면서 근사화 방법을 사용하고 있다. 이 경우 MPS/LPS의 구간이 뒤바뀌는 경우가 발생하며 출력비트가 늘어날 수 있다. 본 논문에서는 이러한 문제점을 완화하기 위하여 근사식을 사용하는 대신에 룩업테이블 형태로 AQe의 값을 양자화하여 계산에 적용하는 방법을 제안하고자 한다. 제안한 방법의 압축 성능을 실험을 통해 확인한 결과, 2진영상 압축표준 방식인 JBIG2의 경우 약 4%의 압축율의 개선을 보였다. 정지영상 압축표준인 JPEG2000의 경우 약 1%정도의 개선을 가져왔다. 룩업테이블을 사용하기 때문에 계산량이 기존방법에 비해 늘지 않는다.

Binary MQ arithmetic coding is widely used recently as a basic entropy coder in multimedia coding system. MQ coder esteems high in compression efficiency to be used in JBIG2 and JPEG2000. The importance of arithmetic coding is increasing after it is adopted as an unique entropy coder in HEVC standard. In the binary MQ coder, arithmetic approximation without multiplication is used in the process of recursive subdivision of range interval. Because of the MPS/LPS exchange activity happened in MQ coder, output byte tends to increase. This paper proposes an enhanced binary MQ arithmetic coder to make use of a lookup table for AQe using quantization skill in order to reduce the deficiency. Experimental results show that about 4% improvement of compression in case of JBIG2 for bi-level image compression standard. And also, about 1% improvement of compression ratio is obtained in case of lossless JPEG2000 coding. For the lossy JPEG2000 coding, about 1% improvement of PSNR at the same compression ratio. Additionally, computational complexity is not increasing.

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참고문헌

  1. J. J. Rissanen, "Generalized Kraft inequality and arithmetic coding," IBM Journal of Research & Development, Vol. 20, pp. 198-203. 1976. https://doi.org/10.1147/rd.203.0198
  2. X. Tian, T.M. Le, and Y. Lian, Review of CAVLC, arithmetic coding, and CABAC, in Entropy Coders of the H.264/AVC Standard, 1st ed. Berlin: Springer, ch. 2, pp. 29-39, 2011.
  3. N. Abramson. Information Theory and Coding, 1st ed. New York, NY: McGraw-Hill, 1963.
  4. I. H. Witten, R. M. Neal, and J. G. Cleary, “Arithmetic coding for data compression,” Communication of the ACM, Vol. 30, No. 6, pp. 520-540, June 1987. https://doi.org/10.1145/214762.214771
  5. G. G. Langdon, Jr, "An introduction to arithmetic coding," IBM Journal of Research & Development, Vol. 28 No. 2 pp. 135-149, March 1984 https://doi.org/10.1147/rd.282.0135
  6. P. G. Howard and J. S. Vitter, "Arithmetic coding for data compression," Proceedings of IEEE, Vol. 82, No. 6, pp. 856-865, June 1994.
  7. A. Moffat, R.M Neal, and H. Witten, "Arithmetic coding, revisited," ACM Transaction on Information Systems, 16(3), pp. 256-294, July 1998. https://doi.org/10.1145/290159.290162
  8. A. Said, "Introduction to arithmetic coding: theory and practice, technical report," HPL-2004-76, HP Laboratories, Palo Alto, USA, 2004.
  9. W. B. Pennebaker, J. L. Mitchell, G. G. Langdon Jr., and R. B. Arps, “An overview of the basic principles of the Q-coder adaptive binary arithmetic coder,” IBM Journal of Research and Development, Vol. 32, No. 6, pp. 717-726, 1988. https://doi.org/10.1147/rd.326.0717
  10. ITU-T Recommendation T.81, Information technology - digital compression and coding of continuous-tone still images - requirements and guidelines, 1993.
  11. ITU-T Recommendation T.82, Information technology - coded representation of picture and audio information - progressive bi-level image compression, March 1993.
  12. ITU-T Recommendation T.88, Information technology-lossy/lossless coding of bi-level images, 2000.
  13. ITU-T Recommendation T.89, Application profiles for recommendation T.88 - lossy/lossless coding of bi-level images for facsimile, Sept. 2001.
  14. ISO/IEC 15444-1:2004, Information technology - JPEG 2000 image coding system: Part 1: core coding system, 2004.
  15. D. Marpe, Fast adaptive binary arithmetic coding (M Coder) [internet] Available: http://iphome.hhi.de/marpe/mcoder.htm
  16. D. Marpe and T. Wiegand, "A highly efficient multiplication-free binary arithmetic coder and its application in video coding," Proceedings IEEE International. Conference Image Processing (ICIP), Barcelona, Spain, September 2003.
  17. D. Marpe, H. Schwartz, and T. Wigland, “Context-based adaptive binary arithmetic coding in the H.264/AVC video compression standard,” IEEE Transactions on Circuits and Systems for Video Technology, Vol. 13, No. 17, pp. 620-636, July, 2003. https://doi.org/10.1109/TCSVT.2003.815173
  18. D. Marpe, G. Marten, and H. L. Cycon, "A fast renormalization technique for H.264/MPEG4-AVC arithmetic coding," in Proceedings 51st Internationales Wissenschaftliches Kolloquium (IWK), Ilmenau University of Technology, Ilmenau: Germany, Sept. 2006
  19. Michael Adams, JPEG2000 Jasper project, University of Victoria. [internet], Available: http://www.ece.uvic.ca/-frodo/jasper/