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BTC-based Image Compression using Pattern

패턴을 이용한 블록 절단 부호화 기반의 영상 압축

  • 김천식 (안양대학교 디지털미디어공학과) ;
  • 오재환 (안양대학교 정보통신공학과)
  • Received : 2015.02.09
  • Accepted : 2015.06.12
  • Published : 2015.06.30

Abstract

Block Truncation Coding, or BTC, is a type of lossy image compression technique for grayscale images. It divides the original images into blocks and then reduces the number of grey levels in each block to compute the mean and standard deviation. BTC has also been adapted to video compression. Another variation of BTC is Absolute Moment Block Truncation Coding. AMBTC is computationally simpler than BTC. In this paper, we proposed new image compression method based on BTC, which is applied patterns to improve compression rate and image quality. This method make two codebooks to extract 36 and 64 patterns from the highest frequency patterns in BTC. When you are compressing an image, you compare many block patterns to that of codebook and use to compress indexes of identical patterns. We experiment our proposed scheme with 36 patterns and the experimental results showed the compression rate of 1.37 bpp. In this paper, our proposed scheme showed higher compression rate rather than that of BTC. In experiment, we used standard images for the performance evaluation.

블록절단 코딩 또는 BTC(Block Truncation Coding)는 회색 영상을 위한 손실 영상 압축 기술의 일종이다. 이 방법은 원본 영상을 여러 개의 블록으로 나누고 각 블록에 대해서 평균과 표준편차를 계산하여 각 블록에서의 회색 레벨의 수를 줄인다. BTC는 비디오 압축에 적합하도록 만들어졌다. BTC의 변형된 것으로 AMBTC (Absolute Moment Block Truncation Coding)가 있다. AMBTC는 BTC보다 계산이 간편하다. 본 논문에서는 압축 성능과 이미지 해상도를 높이기 위해서 패턴을 활용한 BTC 기반의 이미지 압축방법을 제안하고자 한다. 이 방법은 여러 이미지의 BTC에 빈도수가 높은 패턴 36개와 64개를 추출하여 코드 북을 만든다. 이미지를 압축할 때 해당 블록과 패턴을 비교해서 일치하는 패턴의 인덱스를 압축에 이용하는 방법이다. 제안한 방법을 실험하였고 36개의 패턴을 활용할 경우 1.37bpp의 압축 성능을 보였다. 본 논문에서 제안한 방법은 BTC 압축보다 높은 성능을 보였다. 제안한 방법의 성능은 표준 이미지를 이용하여 실험하였다.

Keywords

References

  1. C. Kim, "Data Hiding Based on BTC using EMD," The Journal of The Institute of Internet, Broadcasting and Communication (IIBC), vol.14, no.2, pp.11-16, 2014. https://doi.org/10.7236/JIIBC.2014.14.2.11
  2. Meftah M.Almrabet, Amer R. Zerek, Allaoua Chaoui and Ali A. Akash, "Image Compression using Block Truncation Coding," International Journal of Sciences and Techniques of Automatic control & computer engineering, vol.3, no.2, pp.1046-1053, 2009.
  3. Pasi Franti, Olli Nevalainen, Timo Kaukoranta, "Compression of Digital Images by Block Truncation Coding: A Survey," The Computer Journal, vol.37, no.4, pp.308-332, 1994. https://doi.org/10.1093/comjnl/37.4.308
  4. W.B.Pennebaker and J.L.Mitchell, "JPEG Still Image Data Compression Standard," New York, Van Nosttrand Reinhold, ISBN:0442012721, 1992.
  5. M.Rabbani and R.Joshi, "An overview of the JPEG 2000 Still Image Compression Standard," Signal Processing and Image Communication, vol. 17, pp. 3-48, 2002. https://doi.org/10.1016/S0923-5965(01)00024-8
  6. K.Somasundram and S.Vimala, "Efficient Block Truncation Coding," International Journal on Computer Science and Engineering, Vol. 02, No. 06, pp.2163-2166, 2010.
  7. G.Arce and N.C.Jr.Gallagher, "BTC Image Coding using Median Filter Roots," IEEE Transactions on Communication, vol. 31, no. 6, pp. 784-793, 1983. https://doi.org/10.1109/TCOM.1983.1095885
  8. Yung-Gi Wu, "Block Truncation Image Bitplane Coding," SPIE, Optical Engineering, vol. 41, no. 10, pp. 2476-2478, 2002. https://doi.org/10.1117/1.1503345
  9. Pasti Franti and Olli Nevalainen, "Block Truncation Coding with Entropy Coding," IEEE Transaction on Communications, vol.43, no.2, 1995.
  10. Lucas Hui, "An Adaptive Block Truncation Coding Algorithm for Image Compression," Acoustics, Speech, and Signal Processing (ICASSP-90), vol.4, pp.2233-2235, 1990.
  11. Y.V.Ramana Rao and C.Eswaran, "A new algorithm for BTC image bit plane coding," IEEE Transactions on Communications, vol.43, no.6, pp.2010-2011, 1995. https://doi.org/10.1109/26.387439
  12. Maximo D.Lema, O.Robert Mitchell, "Absolute Moment Block Truncation Coding and its Application to Color Images," IEEE Transactions on Communications, vol.32, no.10, pp.1148-1157, 1984. https://doi.org/10.1109/TCOM.1984.1095973
  13. Madhu Shandilya and Rajesh Shandilya, "Implementation of Absolute moment Block Truncation Coding Scheme Based on Mean Square Error Criterion," SDR 03 Technical Conference and Product Exposition.
  14. K.Somasundaram and I.Kaspar Raj, "Low Computational Image Compression Scheme based on Absolute Moment Block Truncation Coding," World Academy of Science, Engineering and Technoloy, vol. 19, pp. 166-171, 2006.
  15. N.M.Nasrabadi and R.B.King, "Image Coding using Vector Quantization: A Review," IEEE Transactions on Communication, vol.36, no.8, pp. 957-971, 1998.
  16. B.H. Lee, "Technique for production and encoding of New dot-type Print Watermark Pattern," Journal of the Korea Academia Industrial cooperation Society, vol.10, no.5, pp.979-984, 2009. https://doi.org/10.5762/KAIS.2009.10.5.979