(Publisher of Peer Reviewed Open Access Journals)

International Journal of Advanced Computer Research (IJACR)

ISSN (Print):2249-7277    ISSN (Online):2277-7970
Volume-7 Issue-28 January-2017
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DOI:10.19101/IJACR.2017.728007
Paper Title : Tri-mode dual level 3-D image compression over medical MRI images
Author Name : D. J. Ashpin Pabi, P. Aruna and N.Puviarasan
Abstract :

Digital image sequence requires huge storage and high bandwidth for transmitting data in uncompressed form of the multimedia communication. Efficient image compression technique is required to meet the acceptable quality. In this paper, an efficient image compression technique is developed based on the intensity value of the pixels. The proposed image compression algorithm contains two levels of compression. Initially the average between the neighboring of a particular pixel is evaluated and it is assigned to the pixels of the original image. This reduces the correlations of the intensity level. The same pixel assignment is extended towards three dimensional forms along rows, column and the diagonals. To retain the quality of the image the compressed image based on such intensity assignment is encoded using the proposed tri-mode encoding scheme. The encoded bits are decoded at the compression decoder. To reveal the efficiency of the proposed method, the obtained results are compared with the other existing methods. The proposed algorithm has been tested in magnetic resonance imaging (MRI) images of the brain. Simulation results show the proposed method gives the best results over the other existing methods.

Keywords : Image compression, Magnetic resonance images, Color images, Histogram processing, Encoding schemes.
Cite this article : D. J. Ashpin Pabi, P. Aruna and N.Puviarasan, " Tri-mode dual level 3-D image compression over medical MRI images " , International Journal of Advanced Computer Research (IJACR), Volume-7, Issue-28, January-2017 ,pp.8-14.DOI:10.19101/IJACR.2017.728007
References :
[1]Moonen M, Van Dooren P, Vandewalle J. A singular value decomposition updating algorithm for subspace tracking. SIAM Journal on Matrix Analysis and Applications.1992;13(4):1015-38.
[Crossref] [Google Scholar]
[2]Kahu S, Rahate R. Image compression using singular value decomposition. International Journal of Advancements in Research & Technology. 2013;2(8):244-8.
[Google Scholar]
[3]Konda T, Nakamura Y. A new algorithm for singular value decomposition and its parallelization. Parallel Computing. 2009;35(6):331-44.
[Crossref] [Google Scholar]
[4]Andrews H, Patterson C. Singular value decompositions and digital image processing. IEEE Transactions on Acoustics, Speech, and Signal Processing. 1976;24(1):26-53.
[Crossref] [Google Scholar]
[5]Kamm JL. SVD-based methods for signal and image restoration (Doctoral dissertation, PhD thesis).1998.
[Google Scholar]
[6]Yang JF, Lu CL. Combined techniques of singular value decomposition and vector quantization for image coding. IEEE Transactions on Image Processing. 1995;4(8):1141-6.
[Crossref] [Google Scholar]
[7]Hu A, Zhang R, Yin D, Zhan Y. Image quality assessment using a SVD-based structural projection. Signal Processing: Image Communication. 2014;29(3):293-302.
[Crossref] [Google Scholar]
[8]Gupta P, Purohit GN, Bansal V. A survey on image compression techniques. International Journal of Advanced Research in Computer and Communication Engineering. 2014;3(8):7762-8.
[Google Scholar]
[9]Shih YT, Chien CS, Chuang CY. An adaptive parameterized block-based singular value decomposition for image de-noising and compression. Applied Mathematics and Computation. 2012;218(21):10370-85.
[Crossref] [Google Scholar]
[10]Zhang YJ, Li SH, Wang SL. Detecting shifted double JPEG compression tampering utilizing both intra-block and inter-block correlations. Journal of Shanghai Jiaotong University (Science). 2013;18(1):7-16.
[Crossref] [Google Scholar]
[11]Rufai AM, Anbarjafari G, Demirel H. Lossy image compression using singular value decomposition and wavelet difference reduction. Digital Signal Processing. 2014;24:117-23.
[Crossref] [Google Scholar]
[12]ZainEldin H, Elhosseini MA, Ali HA. Image compression algorithms in wireless multimedia sensor networks: a survey. Ain Shams Engineering Journal. 2015;6(2):481-90.
[Crossref] [Google Scholar]