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Multimedia Tools and Applications

, Volume 78, Issue 1, pp 27–45 | Cite as

Near lossless coding of sparse histogram images based on zero-skip quantization

  • Sayaka MinewakiEmail author
  • Masahiro Iwahashi
  • Hiroyuki Kobayashi
  • Taichi Yoshida
  • Hitoshi Kiya
Article

Abstract

This paper introduces a zero-skip quantization (ZS.Q) scheme for the near lossless coding of sparse histogram images. Increases in the range of pixel values and various tone mapping operations on those pixel values mean that the histogram bins often contain no pixels. Recently, this sparseness of the histogram was used to increase the lossless coding performance by introducing histogram packing. This approach was extended to lossy coding by combining spatial quantization and lossless coding. However, such methods do not satisfy the near lossless (NL) condition. In contrast, conventional NL coding such as the JPEG-LS standard satisfies the NL condition, but does not use the histogram sparseness. In this paper, a simple ZS.Q procedure is introduced that uses the histogram sparseness to increase coding efficiency under the NL condition. The proposed method has the following advantages: 1) It guarantees the maximum quantization error is less than some threshold; 2) It can be combined with an arbitrary lossless encoder, such as lossless JPEG 2000 or lossless JPEG-LS; 3) Coding errors do not accumulate under repeat encoding and decoding.

Keywords

Data compression Image coding Quantization Jpeg 

Notes

Acknowledgements

This work was supported in part by a Japan Society for the Promotion of Science Grant-in-Aid KAKENHI Grant Number 23560445.

References

  1. 1.
    Adams MD, Kossentini F (2000) JasPer: a software-based JPEG-2000 codec implementation. In: Proc. IEEE International Conference on Image Processing, Vancouver, vol. 2, pp 53–56, Sept. 2000Google Scholar
  2. 2.
    Aguzzi M, Albanesi M (2006) A novel approach to sparse histogram image lossless compression using JPEG 2000. Electron Lett Comp Vision Image Anal 5(4):24–46CrossRefGoogle Scholar
  3. 3.
    Asif MT, Srinivasan K, Mitrovic N, Dauwels J, Jaillet P (2015) Near-lossless compression for large traffic networks. IEEE Trans Intell Transp Syst 16(4):1817–1826CrossRefGoogle Scholar
  4. 4.
    Bazhyna A, Egiazarian K (2008) Lossless and near lossless compression of real color filter array data. IEEE Trans Consum Electron 54(4):1492–1500CrossRefGoogle Scholar
  5. 5.
    Beerten J, Blanes I, Serra-Sagristà J (2015) A fully embedded two-stage coder for hyperspectral near-lossless compression. IEEE Geosci Remote Sens Lett 12(8):1775–1779CrossRefGoogle Scholar
  6. 6.
    Britanak V, Yip PC, Rao KR (2006) Discrete cosine and sine transforms: general properties, fast algorithms and integer approximations, 1st edn. Academic Press, San DiegoGoogle Scholar
  7. 7.
    Chen YJ, Oriantara S, Nguyen T (2000) Video compression using integer DCT. In: Proc. IEEE International Conference on Image Processing, Vancouver, vol. 2, pp 844–847, Sept. 2000Google Scholar
  8. 8.
    Chien CY, Huangm SC, Pan CH, Fang CM, Chen LG (2009) Pipelined arithmetic encoder design for lossless JPEG XR encoder. In: Proc. IEEE International Symposium on Consumer Electronics, Kyoto, pp 144–147, May 2009Google Scholar
  9. 9.
    Chou CH, Liu KC (2008) Colour image compression based on the measure of just noticeable colour difference. IET Image Process 2(6):304–322MathSciNetCrossRefGoogle Scholar
  10. 10.
    Christopoulos C, Skodras A, Ebrahimi T (2000) The JPEG 2000 still image coding system: an overview. IEEE Trans Consum Electron 46(4):1103–1127CrossRefGoogle Scholar
  11. 11.
    Chuah S, Dumitrescu S, Wu X (2013) L2 optimized predictive image coding with l infinity bound. IEEE Trans Image Processing 22(12):5271–5281CrossRefGoogle Scholar
  12. 12.
    Dang DK, Ohnishi M, Iwahashi M, Chochaitam S (2005) A new structure of integer DCT least sensitive to finite word length expression of multipliers. In: Proc. IEEE International Conference on Image Processing, Genoa, vol. 2, pp 269–272, Sept. 2005Google Scholar
  13. 13.
    Ferreira PJSG, Pinho AJ (2002) Why does histogram packing improve lossless compression rates? IE.EE Signal Processing Lett 9(8):259–261CrossRefGoogle Scholar
  14. 14.
    Fujiyoshi M, Kiya H (2015) A near-lossless image compression system with data hiding capability. In: Proc. Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, Hong Kong, pp 1280–1286, Dec. 2015Google Scholar
  15. 15.
    Grecos C, Jiang J, Edirisinghe EA (2001) Two low cost algorithms for improved diagonal edge detection in JPEG-LS. IEEE Trans Consum Electron 47(3):466–473CrossRefGoogle Scholar
  16. 16.
    ISO/IEC 14495-1: 1999 (1999) Information technology - Lossless and near-lossless compression of continuous-tone still images: Baseline. Dec. 1999Google Scholar
  17. 17.
    ISO/IEC 15444-1:2004 (2004) Information technology - JPEG 2000 image coding system: Core coding system. pp 1–194Google Scholar
  18. 18.
    Iwahashi M, Kiya H (2012) Efficient lossless bit depth scalable coding for HDR images. In: Proc. Signal & Information Processing Association Annual Summit and Conference, Hollywood, pp 1–4, Dec. 2012Google Scholar
  19. 19.
    Iwahashi M, Kiya H (2012) Avoidance of singular point in integer orthonormal transform for lossless coding. IEEE Trans Signal Process 60(5):2648–2653MathSciNetCrossRefGoogle Scholar
  20. 20.
    Iwahashi M, Kiya H (2013) Two layer lossless coding of HDR images. In: Proc. IEEE International Conference on Acoustics, Speech, and Signal Processing, Vancouver, pp 1340–1344, May 2013Google Scholar
  21. 21.
    Iwahashi M, Nakagawa K, Chokchaitam S, Tonomura Y (2004) Theoretical analysis on optimum word length assignment for integer DCT. In: Proc. IEEE International Conference on Image Processing, Singapore, vol. 4, pp 2507–2510, Oct. 2004Google Scholar
  22. 22.
    Iwahashi M, Ogawa M, Kiya H (2011) Lossless integer color transform for four color components. In: Proc. IEEE Visual Communications and Image Processing, Tainan, pp 1–4, Nov. 2011Google Scholar
  23. 23.
    Iwahashi M, Kobayashi H, Kiya H (2012) Lossy compression of sparse histogram image. In: Proc. IEEE International Conference on Acoustics, Speech and Signal Processing, Kyoto, pp 1361–1364, March 2012Google Scholar
  24. 24.
    Iwahashi M, Kobayashi H, Kiya H (2012) Fine rate control and high SNR coding for sparse histogram images. In: Proc. Picture Coding Symposium, Krakow, pp 205–208, May 2012Google Scholar
  25. 25.
    Iwahashi M, Orachon T, Kiya H (2013) Three dimensional discrete wavelet transform with deduced number of lifting steps. In: Proc. IEEE International Conference on Image Processing, Melbourne, pp 1651–1654, Sept. 2013Google Scholar
  26. 26.
    Iwahashi M, Orachon T, Kiya H (2013) Non separable 3D lifting structure compatible with separable quadruple lifting DWT. In: Proc. Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, Kaohsiung, pp 1–4, Oct. 2013Google Scholar
  27. 27.
    Jeong H, Kim J, Lee K, Yoo K, Kim J (2012) Lossless embedded compression algorithm with context-based error compensation for video application. In: Proc. IEEE International Symposium on Consumer Electronics, Harrisburg, pp 1–4, June 2012Google Scholar
  28. 28.
    Ke L, Marcellin MW (1998) Near-lossless image compression: minimum-entropy, constrained-error DPCM. IEEE Trans Image Process 7(2):225–228MathSciNetCrossRefGoogle Scholar
  29. 29.
    Li X, Orchard MT (2001) Edge-directed prediction for lossless compression of natural images. IEEE Trans Image Process 10(6):813–817CrossRefGoogle Scholar
  30. 30.
    Nasr Esfahani E, Samavi S, Karimi N, Shiran S (2008) Near lossless image compression by local packing of histogram. In: Proc. IEEE International Conference on Acoustics, Speech and Signal Processing, Las Vegas, pp 1197–1200, March 2008Google Scholar
  31. 31.
    Penna B, Tillo T, Magli E, Olmo G (2006) Progressive 3-D coding of hyperspectral images based on JPEG 2000. IEEE Geosci, Remote Sen Lett 3(1):125–129CrossRefGoogle Scholar
  32. 32.
    Pinho AJ (2002) An online preprocessing technique for improving the lossless compression of images with sparse histograms. IEEE Signal Process Lett 9(1):5–7CrossRefGoogle Scholar
  33. 33.
    Poomrittigul S, Ogawa M, Iwahashi M, Kiya H (2013) Reversible color transform for Bayer color filter array images. APSIPA Trans Signal Inf Process 2:1–10CrossRefGoogle Scholar
  34. 34.
    Qian SE, Bergeron M, Cunningham I, Gagnon L, Hollinger A (2006) Near lossless data compression onboard a hyperspectral satellite. IEEE Trans Aerosp Electron Syst 42(3):851–866CrossRefGoogle Scholar
  35. 35.
    Reinhard E, Ward G, Pattanaik S, Debevec P, Heidrich W, Myszkowski K (2010) High dynamic range imaging - acquisition, display and image based lighting, 2nd edn. Morgan Kaufmann, BurlingtonGoogle Scholar
  36. 36.
    Santa Cruz D, Ebrahimi T (2000) An analytical study of JPEG 2000 functionalities. In: Proc. International Conference on Image Processing, Vancouver, vol. 2, pp. 49–52, Sept. 2000Google Scholar
  37. 37.
    van der Schaar M, de With PHN (2000) Near-lossless complexity-scalable embedded compression algorithm for cost reduction in DTV receivers. IEEE Trans Consum Electron 46(4):923–933CrossRefGoogle Scholar
  38. 38.
    Son CH, Kim JW, Song SG, Park SM, Kim YM (2010) Low complexity embedded compression algorithm for reduction of memory size and bandwidth requirements in the JPEG 2000 encoder. IEEE Trans Consum Electron 56(4):2421–2429CrossRefGoogle Scholar
  39. 39.
    Taquet J, Labit C (2012) Hierarchical oriented predictions for resolution scalable lossless and near-lossless compression of CT and MRI biomedical images. IEEE Trans Image Process 21(5):2641–2652MathSciNetCrossRefGoogle Scholar
  40. 40.
    Ward G, Simmons M (2005) JPEG-HDR: A backwards-compatible, high dynamic range extension to JPEG. In: Proc. Color Imaging Conference, Arizona, pp 1–8, Nov. 2005Google Scholar
  41. 41.
    Weinberger MJ, Seroussi G, Sapiro G (2000) The LOCO-I lossless image compression algorithm: principles and standardization into JPEG-LS. IEEE Trans Image Process 9(8):1309–1324CrossRefGoogle Scholar
  42. 42.
    Wu X, Bao P (2000) L infinity constrained high-fidelity image compression via adaptive context modeling. IEEE Trans Image Process 9(4):536–542CrossRefGoogle Scholar
  43. 43.
    Wu X, Memon N (1996) CALIC - A context based adaptive lossless image codec. In: Proc. IEEE International Conference on Acoustics, Speech, and Signal Processing. Atlanta, vol. 4, pp 1890–1893, May 1996Google Scholar
  44. 44.
    Xiong Z, Wu X, Cheng S, Hua J (2003) Lossy-to-lossless compression of medical volumetric data using three-dimensional integer wavelet transforms. IEEE Trans Med Imaging 22(3):459–470CrossRefGoogle Scholar
  45. 45.
    Xu R, Pattanaik SN, Hughes CE (2005) High-dynamic-range still image encoding in JPEG 2000. IEEE Comput Graph Appl 25(6):57–64CrossRefGoogle Scholar
  46. 46.
    Yng TLB, Lee BG, Yoo H (2008) A low complexity and lossless frame memory compression for display devices. IEEE Trans Consum Electron 54(3):1453–1458CrossRefGoogle Scholar
  47. 47.
    Zhang Y, Agrafiotis D, Bull DR (2013) High dynamic range image & video compression a review. In: Proc. International Conference on Digital Signal Processing, Santorini, pp 1–7, July 2013Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2017

Authors and Affiliations

  1. 1.National Institute of TechnologyYuge CollegeOchiJapan
  2. 2.Nagaoka University of TechnologyNiigataJapan
  3. 3.Tokyo Metropolitan College of Industrial TechnologyTokyoJapan
  4. 4.Tokyo Metropolitan UniversityTokyoJapan

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