A refined modified read compression technique for efficient sharing of multimedia data

  • Authors

    • T Kavitha Osmania University
    • K Jaya Sankar Osmanaia University
    2019-02-25
    https://doi.org/10.14419/ijet.v7i4.15022
  • Cloud Computing, Compression Technique, Huffman Code, Modified READ, Neural Network.
  • Abstract

    Compression technique expedites in solving many of the research problems for storage and sharing of multimedia data over the wireless channel. Many applications such as UIDAI (Unique Identification Authority of India) and Digi Locker adopts cloud platform. The digital data such as fingerprint, iris, driving license, school certificates are scanned, encrypted and stored in cloud platform. These applications require lossless compression. Modified Huffman (MH) encoding is the most preferred technique to achieve lossless compression. However, the existing MH encoding technique suffers due to numerous codewords of large bit lengths thus effecting performance. Modified READ (MR) and Machine learning techniques are used by the state-of-art technique compression algorithms to achieve better compression. However, they incur computation overhead. To improve the compression ratio and reduce the processing time, a Refined Modified READ (RMR) encoding scheme is presented, the encoding is done using Refined Huffman (RH) by encoding the pixels diagonally instead of encoding the pixels horizontally. Then the subsequent lines are encoded using RMR in parallel fashion and in both directions, which helps in reducing the computation time. Experimental outcome shows that RMR achieves significant improvement in compression ratio over its predecessor and as well as many of the state-of-art technique compression algorithms like Lempel-Ziv-Welch (LZW), Joint Bi-level Image Group 2 (JBIG2) and Neural network-based compression technique Levenberg–Marquardt (LM) back propagation algorithm.

     

     


  • References

    1. [1] NEMA PS3 / ISO 12052, Digital Imaging and Communications in Medicine (DICOM) Standard, Rosslyn, VA, USA: National Electrical Manufacturers Association.USA.

      [2] Gonzalez, R.C., Woods, R.E.: ‘Digital image processing’ (Pearson Education, 2008, 3rd edn.).

      [3] S. Parikh, H. Kalva and V. Adzic, "Evaluation of HEVC compression for high bit depth medical images," IEEE International Conference on Consumer Electronics (ICCE), Las Vegas, NV, pp. 311-314, 2016. https://doi.org/10.1109/ICCE.2016.7430625.

      [4] S. Parikh; D. Ruiz; H. Kalva; G. Fernandez-Escribano; v. Adzic, "High Bit-Depth Medical Image Compression with HEVC," in IEEE Journal of Biomedical and Health Informatics , vol.PP, no.99, pp.1-1, 2017.

      [5] G. J. Sullivan, J. R. Ohm, W. J. Han and T. Wiegand. Overview of the High Efficiency Video Coding (HEVC) Standard. IEEE Transactions on Circuits and Systems for Video Technology. 22(12), pp. 1649-1668, 2012. https://doi.org/10.1109/TCSVT.2012.2221191.

      [6] P. Enfedaque; F. Auli-Llinas; J. C. Moure, "GPU Implementation of Bitplane Coding with Parallel Coefficient Processing for High Performance Image Compression," in IEEE Transactions on Parallel and Distributed Systems , vol.PP, no.99, pp.1-1. 2017.

      [7] F. Aulí-Llinà s, "Context-Adaptive Binary Arithmetic Coding With Fixed-Length Codewords," in IEEE Transactions on Multimedia, vol. 17, no. 8, pp. 1385-1390, 2015. https://doi.org/10.1109/TMM.2015.2444797.

      [8] Zribi, R. Pyndiah, S. Zaibi, F. Guilloud and A. Bouallegue, "Low-Complexity Soft Decoding of Huffman Codes and Iterative Joint Source Channel Decoding," in IEEE Transactions on Communications, vol. 60, no. 6, pp. 1669-1679, 2012. https://doi.org/10.1109/TCOMM.2012.041212.100330.

      [9] H. C. Kuo and Y. L. Lin, "A Hybrid Algorithm for Effective Lossless Compression of Video Display Frames," in IEEE Transactions on Multimedia, vol. 14, no. 3, pp. 500-509, 2012. https://doi.org/10.1109/TMM.2012.2191945.

      [10] D. A. Huffman, “A method for the construction of minimum redundancy codes,†Proc. I.R.E., vol. 40, no. 9, pp. 1098–1102, Sep. 1952. https://doi.org/10.1109/JRPROC.1952.273898.

      [11] K. Wakabayashi, "Research and Events that Permitted Facsimile Use to Explode in Japan," 2009 IEEE Globecom Workshops, Honolulu, HI, 2009, pp. 1-6.

      [12] S. Sahami M.G. Shayesteh, “Bi-level image compression technique using neural networks,†IET Image Process., 2012, Vol. 6, Iss. 5, pp. 496–506.

      [13] T. Kavitha and Dr. K. Jaya Sankar, “An Efficient Compression Technique for ITU-T Group 3 Coded Images Using Variable Length Codes with Reduced Average Lengthâ€, 2016 IEEE International Conference on India International Conference On Information Processing (IICIP-2016) , pp. 1-6.

      [14] Standard Test Images. Compiled by Mike Waken, University of Michigan--ww.ece.rice.edu/~wakin/images.

      [15] Niemi and J. Teuhola, "Interpolative Coding as an Alternative to Arithmetic Coding in Bi-Level Image Compression," SCC 2015; 10th International ITG Conference on Systems, Communications and Coding, Hamburg, Germany, 2015, pp. 1-6.

      [16] Fahad Lateef, Najeem Lawal, Muhammad Imran “Binary Image Compression Algorithms for FPGA Implementation,†International Journal of Scientific & Engineering Research, Volume 7, Issue 3, March-2016.

      [17] K. Khursheed, N. Ahmad, M. Imran and M. O'Nils, "Detecting and coding region of interests in bi-level images for data reduction in Wireless Visual Sensor Network," 2012 IEEE 8th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob), Barcelona, 2012, pp. 705-712. https://doi.org/10.1109/WiMOB.2012.6379153.

      [18] Cinque, L., De Agostino, S. & Lombardi, L. “Binary Image Compression via Monochromatic Pattern Substitution: Sequential and Parallel Implementations,†Math.Comput. Sci. (2013) 7: 155. https://doi.org/10.1007/s11786-013-0153-x.

      [19] Saif al Zahir "Universal lossless compression algorithm for textual images", Opt. Eng. 51(3), 037010 (Apr 09, 2012). https://doi.org/10.1117/1.OE.51.3.037010.

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  • How to Cite

    Kavitha, T., & Jaya Sankar, K. (2019). A refined modified read compression technique for efficient sharing of multimedia data. International Journal of Engineering & Technology, 7(4), 4792-4798. https://doi.org/10.14419/ijet.v7i4.15022