JOURNAL BROWSE
Search
Advanced SearchSearch Tips
High Efficient Entropy Coding For Edge Image Compression
facebook(new window)  Pirnt(new window) E-mail(new window) Excel Download
 Title & Authors
High Efficient Entropy Coding For Edge Image Compression
Han, Jong-Woo; Kim, Do-Hyun; Kim, Yoon;
  PDF(new window)
 Abstract
In this paper, we analyse the characteristics of the edge image and propose a new entropy coding optimized to the compression of the edge image. The pixel values of the edge image have the Gaussian distribution around `0`, and most of the pixel values are `0`. By using this analysis, the Zero Block technique is utilized in spatial domain. And the Intra Prediction Mode of the edge image is similar to the mode of the surrounding blocks or likely to be the Planar Mode or the Horizontal Mode. In this paper, we make use of the MPM technique that produces the Intra Prediction Mode with high probability modes. By utilizing the above properties, we design a new entropy coding method that is suitable for edge image and perform the compression. In case the existing compression techniques are applied to edge image, compression ratio is low and the algorithm is complicated as more than necessity and the running time is very long, because those techniques are based on the natural images. However, the compression ratio and the running time of the proposed technique is high and very short, respectively, because the proposed algorithm is optimized to the compression of the edge image. Experimental results indicate that the proposed algorithm provides better visual and PSNR performance up to 11 times than the JPEG.
 Keywords
Edge Image;Entropy Coding;Compression;Context Based Adaptive Binary Arithmetic Coding;
 Language
Korean
 Cited by
 References
1.
P. B. Khobragade, S. S. Thakare, "Image Compression Techniques- A Review," International Journal of Computer Science and Information Technologies, Vol. 5(1), 2014.

2.
A. Lata, P. Singh, "Review of Image Compression Techniques" International Journal of Emerging Technology and Advanced Engineering, Vol. 3, Issue 7, Jul. 2013.

3.
M. Sathya Deepa and Dr. N. Sujatha, "Image Compression Using MH Encoding," International Journal of Computer Trends and Technology (IJCTT), Vol. 13, NO. 2, Jul. 2014.

4.
M. AL-Ani and F. Awad, "The JPEG Image Compression Algorithm," International Journal of Advances in Engineering & Technology (IJAET), Vol. 6, Issue 3, pp. 1055-1062, Jul. 2013.

5.
K. Wallace, "The JPEG Still Picture Compression Standard," IEEE Transactions on Consumer Electronics, Vol. 38, NO. 1, Feb. 1992.

6.
T. Rabie, "Lossless Quality Steganographic Color Image Compression," International Journal of Advanced Computer Science and Applications, Vol. 6, NO. 4, 2015.

7.
D. Marpe, H. Schwarz, and T. Wiegand, "Context-Based Adaptive Binary Arithmetic Coding in the H.264/AVC Video Compression Standard," IEEE Transactions Circuits and Systems for Video Technology, Vol. 13, NO. 7, pp. 620-636, Jul. 2003. crossref(new window)

8.
G. Sullivan, J. Ohm, W. Han, and T. Wiegand, "Overview of the High Efficiency Video Coding (HEVC) Standard," IEEE Transactions on Circuits and Systems for Video Technology, Vol. 22, NO. 12, Dec. 2012.

9.
V. Sze, and M. Budagavi, "High Throughput CABAC Entropy Coding in HEVC," IEEE Transactions on Circuits and Systems for Video Technology, Vol. 22, NO. 12, Dec. 2012.

10.
D. Marpe, G. Blattermann, T. Wiegand, R. Kurceren, M. Karczewicz, and J. Lainema, "New Results on Improved CABAC," in Joint Video Team of ISO/IEC JTC1/SC29/WG11 & ITU-T SG16/Q.6 Doc. JVTB101, Geneva, Switzerland, Feb. 2002.

11.
D. Marpe, H. Schwarz, G. Blattermann, and T. Wiegand, "Final CABAC Cleanup," in Joint Video Team of ISO/IEC JTC1/SC29/WG11 & ITU-T SG16/Q.6 Doc. JVT-F039, Awaji, Japan, Dec. 2002.

12.
T. Wiegand, G. Sullivan, G. Bjontegaard, and A. Luthra, "Overview of the H.264/AVC Video Coding Standard," IEEE Transactions on Circuits and Systems for Video Technology, Vol. 13, NO. 7, Jul. 2003.

13.
H. Kim, "A Study on the Hardware Design of CABAC for Performance Improvement of HEVC Decoder," Master's Thesis of Hanbat University of Technology, 2013.

14.
Y. Jo, "A Design of Rescheduling and Parallel Architecture for CABAC Decoder in HEVC," Master's Thesis of Kwangwoon University of Technology, 2011.

15.
S. Xue and B. Oelmann "Hybrid Golomb Codes for a Group of Quantised GG Sources," IEE Proceedings - Vision, Image and Signal Processing, Vol. 150, pp. 256-260, Aug. 2003. crossref(new window)