Analysis Review on Image Compression Domain

  • Authors

    • Roshidi Din
    • Alaa Jabbar Qasim
    • Shapina Abdullah
    • Shamsul Jamel Elias
    2019-01-18
    https://doi.org/10.14419/ijet.v8i1.7.25990
  • Compression, Decompression, Lossless Compression, Lossy Compression

  • Abstract

    This paper describes the types of pressure used to decrease the volume of data in lower media. This study is analyzed and categorized according to the two main types of study: Lossy Compression and Lossless compression. Each type has been studied through a number of transactions that determine the efficiency of compression files. The advantages and disadvantages for each type, which emerged from previous researches will also be discussed.

     

  • References

    1. [1] Thyagarajan, K. S. (2011). Still image and video compression with MATLAB. John Wiley & Sons.

      [2] Rao K. R. and Yip, P.(2014). Discrete cosine transform: algorithms, advantages, applications. Academic press.

      [3] Jain, A. K. (1989). Fundamentals of digital image processing. Englewood Cliffs, NJ. Prentice Hall.

      [4] Park, S.G. (2003). Adaptive Lossless Video Compression.

      [5] Rafael, R.E.W. and Gonzalez C. (2008). Digital Image Processing. Pearson Education, Inc.

      [6] UNION, I.T. (1993).mInformation Technology Digital Compression and Coding of Continous-Tone Still Images Requirements and Guidelines.

      [7] Saroya N. and Kaur, P. (2014). Analysis of image compression algorithm using DCT and DWT transforms. International Journal of Advanced Research in Computer Science and Software Engineering, vol. 4.

      [8] Sai Virali Tummala, V.M. (2017). Comparison of Image Compression and Enhancement Techniques for Image Quality in Medical Images. February.

      [9] Wang, Z. Bovik, A. C. Sheikh, H. R.and Simoncelli, E. P. (2004). Image quality assessment: from error visibility to structural similarity. IEEE transactions on image processing, vol. 13, pp. 600-612.

      [10] Deshlahra, A. (2013). Analysis of Image Compression Methods Based On Transform and Fractal Coding.

      [11] Kumar, S. Barnali, B. and Banik, G. (2012). LSB modification and phase encoding technique of audio steganography revisited. International Journal of Advanced Research in Computer and Communication Engineering, vol. 1, pp. 1-4.

      [12] Febryan, A. Purboyo, T.W. and Saputra, R.E.(2017). Steganography Methods on Text, Audio, Image and Video: A Survey. International Journal of Applied Engineering Research, vol. 12, pp. 10485-10490.

      [13] Radhakrishnan, R. Shanmugasundaram, K.and Memon, N.(2002). Data masking: a secure-covert channel paradigm. Multimedia Signal Processing, 2002 IEEE Workshop, pp. 339-342.

      [14] C.Gayathri V.K. (2013). Study on Image Steganography Techniques. International Journal of Engineering and Technology (IJET), May.

      [15] Din, R. and Alaa Jabbar Qasim, A.J. (2018). Analytical Review on Graphical Formats Used in Image Steganographic Compression. Indonesian Journal of Electrical Engineering and Computer Science, vol. Vol 12, No 2, p. pp. 441-446, November.

      [16] Qasim A. J. and Sudhakar, Y. (2015). Information Security with Image through Reversible Room by using Advanced Encryption Standard and Least Significant Bit Algorithm.

      [17] Yip, K. R.(1990). The fast algorithms and applications of the DCT. Academic Press, London.

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  • How to Cite

    Din, R., Jabbar Qasim, A., Abdullah, S., & Jamel Elias, S. (2019). Analysis Review on Image Compression Domain. International Journal of Engineering & Technology, 8(1.7), 293-296. https://doi.org/10.14419/ijet.v8i1.7.25990

    Received date: 2019-01-16

    Accepted date: 2019-01-16

    Published date: 2019-01-18