DOI QR코드

DOI QR Code

고해상도 영상 압축을 위한 SPIHT 기반의 부대역 분할 압축 방법

SPIHT-based Subband Division Compression Method for High-resolution Image Compression

  • 김우석 (광운대학교 전자재료공학과) ;
  • 박병서 (광운대학교 전자재료공학과) ;
  • 오관정 (한국전자통신연구원) ;
  • 서영호 (광운대학교 전자재료공학과)
  • 투고 : 2022.01.21
  • 심사 : 2022.03.07
  • 발행 : 2022.03.30

초록

본 논문에서는 초고해상도를 갖는 복소 홀로그램을 압축하기 위한 전용 코덱에서 SPIHT (set partitioning in hierarchical trees)를 사용할 경우에 발생할 수 있는 문제점을 해결하기 위한 방법을 제안한다. 복소 홀로그램을 위한 코덱의 개발은 크게 전용 압축 방법을 만드는 방법과 HEVC 및 JPEG2000과 같은 앵커 코덱을 이용하고 전후처리 기법을 추가하는 방법으로 구분될 수 있다. 전용 압축 방법을 만드는 경우에 복소 홀로그램의 공간적인 특성을 해석하기 위한 별도의 변환 도구가 필요하다. EZW와 SPIHT 같은 부대역 단위의 제로트리 기반의 알고리즘들은 고해상도의 영상에 대해서 코딩할 경우에 비트스트림 제어 시 온전한 부대역의 정보가 제대로 전송되지 못하는 문제점을 갖는다. 본 논문에서는 이와 같은 문제를 해결하기 위한 웨이블릿 부대역의 분할 방법을 제안한다. 분할한 부대역을 각각 압축하는 것으로 부대역 전역의 정보가 균일하게 유지하도록 한다. 제안하는 방법은 기존 방법에 비하여, PSNR 대비 더 좋은 복원 결과를 보여주었다.

This paper proposes a method to solve problems that may occur when SPIHT(set partition in hierarchical trees) is used in a dedicated codec for compressing complex holograms with ultra-high resolution. The development of codecs for complex holograms can be largely divided into a method of creating dedicated compression methods and a method of using anchor codecs such as HEVC and JPEG2000 and adding post-processing techniques. In the case of creating a dedicated compression method, a separate conversion tool is required to analyze the spatial characteristics of complex holograms. Zero-tree-based algorithms in subband units such as EZW and SPIHT have a problem that when coding for high-resolution images, intact subband information is not properly transmitted during bitstream control. This paper proposes a method of dividing wavelet subbands to solve such a problem. By compressing each divided subbands, information throughout the subbands is kept uniform. The proposed method showed better restoration results than PSNR compared to the existing method.

키워드

과제정보

이 논문은 2022년도 정부(교육부)의 재원으로 한국연구재단의 지원을 받아 수행된 기초연구사업임(2018R1D1A1B07043220).

참고문헌

  1. Dennis Gabor, "A new microscopic principle," Nature, 161, pp. 777-778, 1948. doi: https://doi.org/10.1038/161777a0
  2. P. Hariharan, "Basics of Holography," Cambridge University Press, May 2002.
  3. W. Osten, A. Faridian, P. Gao, K. Korner, D. Naik, G. Pedrini, Al. Kumar Singh, M. Takeda, and M. Wilke, "Recent advances in digital holography [Invited]," Appl. Opt. 53, G44-G63, 2014. doi: https://doi.org/10.1364/AO.53.000G44
  4. H. Yoshikawa, "Digital holographic signal processing," Proc. TAO First International Symposium on Three Dimensional Image Communication Technologies, pp. S-4-2, Dec. 1993. doi: https://doi.org/10.1016/j.image.2018.09.014
  5. JPEG Pleno https://jpeg.org/jpegpleno/
  6. E. Darakis, T. J. Naughton, and J. J. Soraghan, "Compression defects in different reconstructions from phase-shifting digital holographic data," Appl. Opt, vol. 46, no. 21, pp. 4579-4586, Mar. 2007. doi: https://doi.org/10.1364/AO.46.004579
  7. P. Memmolo, M. Paturzo, A. Pelagotti, A. Finizio, P. Ferraro, and B. Javidi, "New high compression method for digital hologram recorded in microscope configuration," In Modeling Aspects in Optical Metrology III. International Society for Optics and Photonics. vol. 8083, no. 80830W, pp. 1-7, May. 2011. doi: https://doi.org/10.1117/12.889520
  8. J. Y. Sim, and C. S. Kim, "Reconstruction depth adaptive coding of digital holograms," IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences, vol. 95, no. 2, pp. 617-620, Feb. 2012. doi: https://doi.org/10.1587/transfun.E95.A.617
  9. T. J. Naughton, Y. Frauel, O. Matoba, N. Bertaux, E. Tajahuerce and B. Javidi, "Three-dimensional imaging, compression, and reconstruction of digital holograms," SPIE Proc, vol. 4877, pp.104-114, Mar. 2003. doi: https://doi.org/10.1117/12.463735
  10. Y. Rivenson, A. Stern, and B. Javidi, "Overview of compressive sensing techniques applied in holography," Applied optics, vol. 52, no. 1, pp. A423-A432, Jan. 2013. doi: https://doi.org/10.1364/AO.52.00A423
  11. H. Zhang, W. Zhou, D. Leber, Z. Hu, X. Yang, P. W. Tsang, and T. C. Poon, " Development of lossy and near-lossless compression methods for wafer surface structure digital holograms," Journal of Micro/Nanolithography, MEMS, and MOEMS, vol. 14, no. 4,pp. 1-8, Dec. 2015. doi: https://doi.org/10.1117/1.JMM.14.4.041304
  12. P. A. Cheremkhin, and E. A. Kurbatova, "Numerical comparison of scalar and vector methods of digital hologram compression," Holography, Diffractive Optics, and Applications VII. vol. 10022, no. 1002227, pp.1-10, Oct. 2016. doi: https://doi.org/10.1117/12.2246411
  13. E. Darakis and J. J. Soraghan, "Compression of interference patterns with application to phase-shifting digital holography," Appl. Opt, vol. 45, no 11, pp. 2437-2443, April. 2006. doi: https://doi.org/10.1364/AO.45.002437
  14. P. A. Cheremkhin, and E. A. Kurbatova, "Quality of reconstruction of compressed off-axis digital holograms by frequency filtering and wavelets," Applied optics, vol.57, no. 1, pp. A55-A64, Jan. 2018. doi: https://doi.org/10.1364/AO.57.000A55
  15. H. Yoshikawa and J. Tamai "Holographic image compression by motion picture coding," SPIE Proc, vol. 2652, Practical Holography X, pp. 2-9, March. 1996. doi: https://doi.org/10.1117/12.236045
  16. Y. H. Seo, H. J. Choi and D. W. Kim, "3D scanning-based compression technique for digital hologram video," Signal Processing: Image Communication, vol. 22, no. 2, pp. 144-156, Nov. 2006. doi: https://doi.org/10.1016/j.image.2006.11.007
  17. Y. H. Seo, H. J. Choi, J. W. Bae, H. J. Kang, S. H. Lee, J. S. Yoo and D. W. Kim, "A new coding technique for digital holographic video using multi-view prediction," IEICE TRANSACTIONS on Information and Systems, vol. E90-D, no.1, pp. 118-125, Jan. 2007. doi: https://doi.org/10.1093/ietisy/e90-1.1.118
  18. E. Darakis and T. J. Naughton, "Compression of digital hologram sequences using MPEG-4," SPIE Proc, vol. 7358, pp. 735811-1, May 2009. doi: https://doi.org/10.1117/12.820632
  19. K. Jaferzadeh, S. Gholami, and I. Moon, "Lossless and lossy compression of quantitative phase images of red blood cells obtained by digital holographic imaging," Applied optics, vol. 55, no. 36, pp. 10409-10416, Dec. 2016. doi: https://doi.org/10.1364/AO.55.010409
  20. W. S. Kim, D. W. Kim, and Y. H. Seo, "Hologram Super-Resolution Using a Single Reverse Inception based Deep Learning," In Proceedings of the Korean Society of Broadcast Engineers Conference, Kwangwoon Square & 80th Anniversary Hall, pp. 214-215, 2019.
  21. W. S. Kim, B. S. Park, J. K. Kim, K. J. Oh, J. W. Kim, D. W. Kim, and Y. H. Seo, "Deep Learning-based Super Resolution for Phase-only Holograms," Journal of Broadcast Engineering, vol. 25, no. 6, pp. 935-943, 2020. doi: https://doi.org/10.5909/JBE.2020.25.6.935