The Journal of Korean Institute of Communications and Information Sciences (한국통신학회논문지)

The Korean Institute of Commucations and Information Sciences (한국통신학회)
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Low Memory Zerotree Coding

저 메모리를 갖는 제로트리 부호화

  • 신철 (광운대학교 전자공학과 디지털 미디어 연구실) ;
  • 김호식 (광운대학교 전자공학과 디지털 미디어 연구실) ;
  • 유지상 (광운대학교 전자공학과 디지털 미디어 연구실)
  • Published : 2002.08.01
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Abstract

The SPIHT(set partitioning in hierarchical tree) is efficient and well-known in the zerotree coding algorithm. However SPIHT's high memory requirement is a major difficulty for hardware implementation. In this paper we propose low-memory and fast zerotree algorithm. We present following three methods for reduced memory and fst coding speed. First, wavelet transform by lifting has a low memory requirement and reduced complexity than traditional filter bank implementation. The second method is to divide the wavelet coefficients into a block. Finally, we use NLS algorithm proposed by Wheeler and Pearlman in our codec. Performance of NLS is nearly same as SPIHT and reveals low and fixed memory and fast coding speed.

SPIHT(set partitioning in hierarchical tree)는 제로트리 알고리즘 중 효율적이며 잘 알려져 있다. 그러나 높은 메모리 요구로 인해 하드웨어 구현에 큰 어려움을 가지고 있다. 본 논문에서는 저 메모리 사용과 빠른 제로트리 부호화 알고리즘을 제안한다. 메모리를 줄이고 빠른 코딩을 위한 방법으로 다음 3가지를 제안한다. 첫 번째, 리프팅(lifting)을 이용한 웨이블릿(wavelet) 변환은 기존의 필터뱅크 방식의 변환보다 저 메모리와 계산량의 감소를 가진다. 두 번째 방법은 웨이블릿 계수들을 블록으로 나누어 각각 부호화 한다. 여기서 블록은 제로트리 구조가 유지되는 STB(spatial tree-based block)이다. 마지막으로 Wheeler와 Pearlmandl 제안한 NLS(no list SPIHT)를 이용한 부호화이다. NLS의 효율성은 SPIHT와 거의 같으며 작고 고정된 메모리와 빠른 부호화 속도를 보여준다.

Keywords

References

  1. A. Said and W. A. Pearlman, 'A new, fast, andeffcient image codec based on set partitioningin hierarchical trees.' IEEE Trans. on Circuitsand Systems for Video Technology, vol.6, pp.243-250, June 1996 https://doi.org/10.1109/76.499834
  2. F.W. Wheeler and W.A. Pearlman 'SPIHTimage compression without lists,' 2000 IEEE International Conference on, vol. 4 , 2000 pp. 2047-2050
  3. J. Shapiro, 'Embedded image coding using zerotrees of wavelet coefficients,' IEEE Trans.On Signal Processing, vo1.41, no.12, pp.3445-3463, December 1993 https://doi.org/10.1109/78.258085
  4. Z.Xiong, K. Ramchandran, and M. Orchard,'Space-frequency quantization for wavelet imagecoding,' IEEE trans. Image Processing, vol. 6,pp. 677-693, May 1997 https://doi.org/10.1109/83.568925
  5. D. Taubman and A. Zakhor, 'Multirate 3-Dsubband coding of video,' IEEE Trans. Image Processing, vol. 3, Sept. 1994, pp. 572-588 https://doi.org/10.1109/83.334984
  6. O. Rioul and M. Vetterli, 'Wavelets and SignalProcessing,' IEEE Signal Processing Magazine,pp. 14-38, 1991
  7. W. Sweldens and P. Schroder. 'Building your own wavelets at home,' Wavelets in Computer Graphics, pp. 15-87, ACM SIGGRAPH Coursenotes, 1996
  8. W. Sweldens, 'The lifting scheme: A Custom-design construction of biorthogonal wavelets,' J.Appl. Comp. Harm. Anal., vol. 3, no. 2, pp.186-200, 1996 https://doi.org/10.1006/acha.1996.0015
  9. M. Antonini, M. Barlaud, P. Mathieu, and I.Daubechies, 'Image coding using wavelettransform,' IEEE trans. Image Processing, vol.1, no.2, pp. 205-220, Apr. 1992 https://doi.org/10.1109/83.136597
  10. I. Daubechies and W. Sweldens, 'Factoringwavelet and subband transforms into liftingsteps,' Journal of Fourier Analysis and Applications, 4(3):245-267, 1998
  11. C. D. Creusere. 'Image coding using parallelimplementation of the embedded zerotreewavelet algorithm,' In Proc. of the IS&T/SPIESymposium om Electronic Imaging, vol. 2668,1996
  12. J. K. Rogeis and P. C. Cosman. 'Waveletzerotree image compression with packetization,'IEEE Signal Processing Letters, 5(5):105-107,May 1998 https://doi.org/10.1109/97.668942
  13. F.W. Wheeler and W.A. Pearlman. 'Low-memory packetized SPIHT image compression,'Conference Record of the Thirty-Third Asilomar Conference on vol. 2, 1999 pp. 1193-1197