전자공학회논문지 IE

대한전자공학회 (The Institute of Electronics and Information Engineers)
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적응적 준무손실 영상 부호화

Adaptive Near-Lossless Image Coding

  • 김영로 (명지전문대학 컴퓨터정보과) ;
  • 이준환 (광운대학교 컴퓨터공학과)
  • Kim, Young-Ro (Department of Computer Science and Information, Myongji College) ;
  • Yi, Joon-Hwan (Department of Computer Engineering, Kwangwoon University)
  • 발행 : 2009.12.25
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⟨ 이전 논문 다음 논문 ⟩

초록

본 논문에서는 전송 대역폭에 따라 손실을 최소화하며 적응적으로 압축률을 조절하는 준무손실 영상 부호화 알고리즘을 제안한다. 제안하는 방법은 슬라이스 부호화 간격으로 부호화된 비트량과 목표 부호화 비트량을 이용하여 적응적으로 허용 오류 범위를 변경한다. 실험 결과, 제안하는 방법은 기존 알고리즘들에 비하여 효과적으로 전송 대역폭에 맞추어 압축률을 조절할 뿐만 아니라 화질 또한 향상됨을 알 수 있다.

In this paper, we propose adaptive near-lossless image coding algorithm according to bandwidth while maintaining image quality. The proposed method adjusts error range using amounts of encoded bits and target bits at a slice encoding interval. Experimental results show that our proposed method not only almost fits compression into bandwidth, but also has better image quality.

키워드

참고문헌

  1. X. Wu and N. Memon, 'Context-based, adaptive, lossless image coding,' IEEE Trans. Communications, vol. 45, no. 4, pp. 437-444, Apr. 1997 https://doi.org/10.1109/26.585919
  2. X. Wu, 'Efficient lossless compression of continuous-tone images via context selection and quantization,' IEEE Trans. Image Processing, vol. 6, pp. 656-664, May 1997 https://doi.org/10.1109/83.568923
  3. X. Wu and N. Memon, 'Context-based lossless interband compression-extending CALIC,' IEEE Trans. Image Processing, vol. 9, no. 6, pp. 994-1001, Jun 2000 https://doi.org/10.1109/83.846242
  4. E. Magli, 'Optimized onboard lossless and near-lossless compression of hyperspectral data using CALIC,' IEEE Geoscience and Remote Sensing Letters, vol. 1, no. 1, pp. 21-25, Jan. 2004 https://doi.org/10.1109/LGRS.2003.822312
  5. W. Ding, F. Wu, X. Wu, and S. Li, 'Adaptive directional lifting-based wavelet transform for image coding', IEEE Trans. on Image Processing, vol. 16, no. 2, Feb. 2007
  6. M. J. Weinberger, J. Rissanen, and R. B. Arps, 'Application of universal context modeling to lossless compression of gray-scale images,' IEEE Trans. Image Processing, vol. 5, pp. 576-586, Apr. 1996
  7. M. J. Weinberger, and G. Seroussi, 'Sequential prediction and ranking in universal context modeling and data compression,' IEEE Trans. Inform. Theory, vol. 43, pp. 1697-1706, Sept. 1997 https://doi.org/10.1109/18.623176
  8. M. J. Weinberger, G. Seroussi, and G. Sapiro, 'The LOCO-I lossless image compression algorithm: principles and standardization into JPEG-LS,' IEEE Trans. Image Processing, vol. 9, no. 8, pp. 1309-1324, Aug. 2000 https://doi.org/10.1109/83.855427
  9. X. Li and M. T. Orchard, 'Edge-directed prediction for lossless compression of natural images,' IEEE Trans. Image Processing, vol. 10, no. 6, pp. 813-817, Jun. 2001 https://doi.org/10.1109/83.923277
  10. S. W. Golomb 'Run-length encodings,' IEEE Trans. Inform. Theory, vol. IT-12, pp. 399-401, Jul. 1966
  11. P. G. Howard and J. S. Vitter, 'Fast and efficient lossless image compression,' in Proc. 1993 Data Compression Conf., Snowbird, UT, Mar. 1993, pp. 351-360
  12. N. D. Memon and K. Sayood, 'Lossless compression of video sequences,' IEEE Trans. Communications, vol. 44, no. 10, pp. 1340-1345, Oct. 1996 https://doi.org/10.1109/26.539775
  13. E. S. G. Carotti and J. C. D. Martin, 'Motion-compensated lossless video coding in the CALIC framework,' Proceedings of the 5th IEEE International Symposium on Signal Processing and Information Technology (ISSPIT), Athens, GR, pp. 600-605, Dec. 2005
  14. G. D. Hann and P. W. A. C. Biezen, 'An efficient true-motion estimator using candidate vectors from a parametric motion medel,' IEEE Trans. Circuits Syst. Video Technol, vol. 8, no. 1, pp. 85-91, Feb. 1998 https://doi.org/10.1109/76.660831
  15. R. B. Wittebrood and G. D. Hann, 'Real-time recursive motion segmentation of video data on a programmable device,' IEEE Trans. on Consumer Electronics, vol. 47, no. 3, pp. 559-567, Aug. 2001 https://doi.org/10.1109/30.964146
  16. S. J. Lee, S. H. LEE, and D. H. Kim, 'Method and apparatus for visually lossless image data compression,' Korea Patent No. 10-2008-0049535, Samsung Electronics Ltd