Skip to main content
SpringerLink
Log in

Adaptive grayscale image coding scheme based on dynamic multi-grouping absolute moment block truncation coding

  • Published:
Multimedia Tools and Applications Aims and scope Submit manuscript

Abstract

Multi-Grouping Absolute Moment Block Truncation Coding (MGAMBTC) technique improve the image quality of Absolute Moment Block Truncation Coding (AMBTC) by adaptively dividing pixels in a block into groups according to block activity. This study found that the bit rate can be reduced further if there is some similarity among the blocks. Therefore, this study proposes a block prediction scheme that exploits the intra-block similarity of neighboring blocks. If a similar encoded block is found, its position code will be stored to encode the block; otherwise, it is encoded with the proposed improved MGAMBTC (iMGAMBTC). The proposed iMGAMBTC employs an entropy-based indicator generation mechanism to reduce the bit rate, and the evaluation demonstrates that the proposed scheme enhances the compression performance of AMBTC and MGAMBTC efficiently.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10

Similar content being viewed by others

References

  1. Arnavut Z, Koc B, Kocak H (2014) “Scanning paths for lossless compression of pseudo-color images,” in Western New York Image and Signal Processing Workshop, pp. 11–14

  2. Chang CC, Hu YC (1998) A fast codebook training algorithm for vector quantization. IEEE Trans Consum Electron 44(4):1201–1208

    Article  Google Scholar 

  3. Chang IC, Hu YC, Chen WL, Lo CC (2015) High capacity reversible data hiding scheme based on residual histogram shifting for block truncation coding. Signal Process 108:376–388

    Article  Google Scholar 

  4. Chang CC, Chen TS, Wang YK, Liu Y (2018) A reversible data hiding scheme based on absolute moment block truncation coding compression using exclusive OR operator. Multimed Tools Appl 77(7):9039–9053

    Article  Google Scholar 

  5. Chen D, Bovik AC (1990) Visual pattern image coding. IEEE Trans Commun 38(12):2137–2146

    Article  Google Scholar 

  6. Chen LG, Liu YC (1994) A high quality MC-OBTC codec for video signal processing. IEEE Trans Circuits Syst Video Technol 4:92–98

    Article  Google Scholar 

  7. Chen WL, Hu YC, Liu KY, Lo CC, Wen CH (2014) Variable-rate quadtree-segmented block truncation coding for color image compression. Int J Signal Process, Image Process Pattern Recognition 7(1):65–76

    Google Scholar 

  8. Dacles MDI, Daga RRM (2018) “Block truncation coding-based audio compression technique,” 2nd International Conference on Digital Signal Processing, pp. 137–141, Tokyo, Japan

  9. Delp EJ, Mitchell OR (1979) Image coding using block truncation coding. IEEE Trans Commun 27:1335–1342

    Article  Google Scholar 

  10. Dhara BC, Chanda B (2004) Block truncation coding using pattern fitting. Pattern Recogn 37:2131–2139

    Article  Google Scholar 

  11. Franti P, Nevalainen P, Kaudoranta T (1994) Compression of digital images by block truncation coding: a survey. Comput J 37:308–332

    Article  Google Scholar 

  12. O. Giudice, D. Allegra, F. Stanco, G. Grasso, S. Battiato, “A fast palette reordering technique based on gpu optimized genetic algorithms,” in IEEE International Conference on Image Processing, pp. 1138–1142, 2018.

  13. Hu YC (2003) Low-complexity and low-bit-rate image compression scheme based on AMBTC. Opt Eng 42:1964–1975

    Article  Google Scholar 

  14. Hu YC (2003) Improved moment preserving block truncation coding for image compression. Electron Lett 39:1377–1379

    Article  Google Scholar 

  15. Hu YC (2004) Predictive moment preserving block truncation coding for graylevel image compression. J Electron Imaging 13:871–877

    Article  Google Scholar 

  16. Hu YC, Su BH, Tsai PY (2008) Coluor image coding scheme using absolute moment block truncation coding and block prediction technique. Imaging Sci J 56(5):254–270

    Article  Google Scholar 

  17. Hu YC, Chuang JC, Lo CC, Lee CY (2011) Efficient grayscale image compression technique based on VQ. Opto-Electron Rev 19(1):104–113

    Article  Google Scholar 

  18. Hu YC, Chen WL, Lo CC, Wu CM (2013) A novel tamper detection scheme for BTC compressed images. Opto-Electron Rev 21(1):137–146

    Article  Google Scholar 

  19. Hu YC, Chen WL, Lo CC, Wu CM, Wen CH (2013) Efficient VQ-based image coding scheme using inverse function and lossless index coding. Signal Process 93(9):2432–2439

    Article  Google Scholar 

  20. Hu YC, Chen WL, Su BH, Chou WK (2013) Dynamic sub-range search methods for image color quantization. Imaging Sci J 61(2):80–93

    Article  Google Scholar 

  21. Hu YC, Chang IC, Liu KY, Hung CL (2014) Improved color image coding schemes based on single bit map block truncation coding. Optical Eng 53(9):093104

    Article  Google Scholar 

  22. Hu YC, Choo KKR, Chen WL (2017) Tamper detection and image recovery for BTC-compressed images. Multimed Tools Appl 76(14):15435–15463

    Article  Google Scholar 

  23. Hu YC, Liu YH, Chang IC (2018) “Color image coding based on block truncation coding using quadtree segmentation," The 3rd International Conference on Computer and Communication Systems (ICCCS 2018), Nagoya institute of technology, Nagoya, Japan

  24. Koc B, Arnavut Z (2011) “Block-sorting transformations with pseudo-distance technique for lossless compression of color-mapped images," in Western New York Image Processing Workshop, pp. 1–4

  25. Lema MD, Mitchell OR (1984) Absolute moment block truncation coding and its application to color image. IEEE Trans Commun 32:1148–1157

    Article  Google Scholar 

  26. Y. H. Lin, C. H. Hsia, B. Y. Chen, Y. Y. Chen, “Visual IoT security: data hiding in AMBTC images using block-wise embedding strategy,” Sensors (Switzerland), Vol. 19, No. 9, Article No 1974, 2019.

  27. Lo CC, Hu YC, Chen WL, Wu CM (2014) Reversible data hiding scheme for BTC-compressed images based on histogram shifting. Int J Secur Appl 8(2):301–314

    Google Scholar 

  28. Nasiopoulos P, Ward RK, Morse DJ (1991) Adaptive compression coding. IEEE Trans Commun 39(7):1245–1254

    Article  Google Scholar 

  29. Olsen SI (2000) Block truncation and planar image coding. Pattern Recogn Lett 21:1141–1148

    Article  Google Scholar 

  30. Pinho J, Neves AJR (2004) A survey on palette reordering methods for improving the compression of color-indexed images. IEEE Trans Image Process 13(11):1411–1418

    Article  MathSciNet  Google Scholar 

  31. Qin C, Ji P, Chang C, Dong J, Sun X (2018) Non-uniform watermark sharing based on optimal iterative BTC for image tampering recovery. IEEE Multimedia 25(3):36–48

    Article  Google Scholar 

  32. Ramana YV, Eswaran C (1995) A new algorithm for BTC bit plane coding. IEEE Trans Commun 43(6):2010–2011

    Article  Google Scholar 

  33. Singh D, Singh SK (2019) Block truncation coding based effective watermarking scheme for image authentication with recovery capability. Multimed Tools Appl 78(4):4197–4215

    Article  Google Scholar 

  34. Tsou CC, Hu YC, Chang CC (2008) Efficient optimal pixel grouping schemes for AMBTC. Imaging Sci J 56(4):217–231

    Article  Google Scholar 

  35. Wang C, Han Y, Wang W (2019) “An end-to-end deep learning image compression framework based on semantic analysis,” Appl Sci, Vol. 9, No. 17, article no. 3580

  36. Wu Y, Coll DC (1992) Single bit-map block truncation coding of color images. IEEE J Select Areas Commun 10(5):952–959

    Article  Google Scholar 

  37. Xiang Z, Hu YC, Yao H, Qin C (2019) Adaptive and dynamic multi-grouping scheme for absolute moment block truncation coding. Multimed Tools Appl 78:7895–7909

    Article  Google Scholar 

  38. Xu Y, Wang Y, Zhou A, Lin W, Xiong H (2018) “Deep neural network compression with single and multiple level quantization,” AAAI Conference on Artificial Intelligence

Download references

Acknowledgments

This research was partially supported by the Ministry of Science and Technology, Taiwan, R.O.C. under project number 106-2410-H-126-006-MY2 and 108-2410-H-020-MY2.

Author information

Authors and Affiliations

  1. Department of Computer Science and Communication Engineering, Providence University, 200 Chung Chi Rd., Taichung, 43301, Taiwan

    Jun-Chou Chuang

  2. Department of Computer Science and Information Management, Providence University, 200 Chung Chi Rd,, Taichung, 43301, Taiwan

    Yu-Chen Hu

  3. Department of Information Management, National Sun Yat-sen University, Kaohsiung, 80424, Taiwan

    Chia-Mei Chen

  4. Key Lab of Intelligent Computing and Signal Processing of Ministry of Education, School of Computer Science and Technology, Anhui University, Hefei, 230601, China

    Zhaoxia Yin

Authors
  1. Jun-Chou Chuang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yu-Chen Hu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Chia-Mei Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Zhaoxia Yin
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Yu-Chen Hu.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Chuang, JC., Hu, YC., Chen, CM. et al. Adaptive grayscale image coding scheme based on dynamic multi-grouping absolute moment block truncation coding. Multimed Tools Appl 79, 28189–28205 (2020). https://doi.org/10.1007/s11042-020-09325-3

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11042-020-09325-3

Keywords

Search

Navigation