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Analysis and comparison of symmetry based lossless and perceptually lossless algorithms for volumetric compression of medical images

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Modern medical imaging techniques produce huge volume of data from stack of images generated in a single examination. To compress them several volumetric compression techniques have been proposed. Performance of these compression schemes can be improved further by considering the anatomical symmetry present in medical images and incorporating the characteristics of human visual system. In this paper a volumetric medical image compression algorithm is presented in which perceptual model is integrated with a symmetry based lossless scheme. Symmetry based lossless and perceptually lossless algorithms were evaluated on a set of three dimensional medical images. Experimental results show that symmetry based perceptually lossless coder gives an average of 8.47% improvement in bit per pixel without any perceivable degradation in visual quality against the lossless scheme.
Rocznik
Tom
Strony
147--154
Opis fizyczny
Bibliogr. 17 poz., rys., tab., wykr.
Twórcy
  • Department of Electrical and Electronics Engineering, Manipal Institute of Technology, Manipal University, 576104, India
autor
  • Department of Electronics and Communication Engineering, National Institute of Technology Karnataka, Surathkal, Mangalore 575025, India
autor
  • Department of Electronics and Communication Engineering, National Institute of Technology Karnataka, Surathkal, Mangalore 575025, India
Bibliografia
  • [1] AIT-AOUDIA S., BENHAMIDA F. Z., YOUSFI M. A. Lossless compression of volumetric medical data. Computer and Information Sciences, 2006. Springer, pp. 563–571.
  • [2] AMRAEE S., KARIMI N., SAMAVI S., SHIRANI S. Compression of 3D MRI images based on symmetry in prediction error field. IEEE International Conference on Multimedia and Expo, 2011. pp. 1–6.
  • [3] BILGIN A., ZWEIG G., MARCELLIN M. W. Efficient lossless coding of medical image volumes using reversible integer wavelet transforms. Proceedings of Data Compression Conference, 1998. pp. 428–437.
  • [4] BRAINWEB. Simulated brain database. 2014.
  • [5] CHANDLER D. M., HEMAMI S. S. VSNR: A wavelet-based visual signal-to-noise ratio for natural images. IEEE Transactions on Image Processing, 2007, Vol. 16. IEEE, pp. 2284–2298.
  • [6] GAUDEAU Y., MOUREAUX J.-M. Lossy compression of volumetric medical images with 3D dead-zone lattice vector quantization. Annals of telecommunications, 2009, Vol. 64. Springer, pp. 359–367.
  • [7] KOWALIK-URBANIAK I., BRUNET D., WANG J., KOFF D., SMOLARSKI-KOFF N., VRSCAY E. R., WALLACE B., WANG Z. The quest for diagnostically lossless medical image compression: a comparative study of objective quality metrics for compressed medical images. SPIE Medical Imaging, 2014, Vol. 9037. pp. 1–17.
  • [8] LOY G., EKLUNDH J. O. Detecting symmetry and symmetric constellations of features. Computer Vision, 2006. Springer, pp. 508–521.
  • [9] RAMASWAMY A., MIKHAEL W. A mixed transform approach for efficient compression of medical images. IEEE Transactions on Medical Imaging, 1996, Vol. 15. IEEE, pp. 343–352.
  • [10] SANCHEZ V., ABUGHARBIEH R., NASIOPOULOS P. 3D scalable lossless compression of medical images based on global and local symmetries. 16th IEEE International Conference on Image Processing, 2009. pp. 2525–2528.
  • [11] SANCHEZ V., ABUGHARBIEH R., NASIOPOULOS P. Symmetry-based scalable lossless compression of 3D medical image data. IEEE Transactions on Medical Imaging, 2009, Vol. 28. IEEE, pp. 1062–1072.
  • [12] SHEIKH H. R., BOVIK A. C. Image information and visual quality. IEEE Transactions on Image Processing, 2006, Vol. 15. IEEE, pp. 430–444.
  • [13] TZANNES A. Compression of 3-dimensional medical image data using part 2 of JPEG 2000. Aware. Inc, Nov, 2003.
  • [14] WANG Z., BOVIK A. C., SHEIKH H. R., SIMONCELLI E. P. Image quality assessment: from error visibility to structural similarity. IEEE Transactions on Image Processing, 2004, Vol. 13. IEEE, pp. 600–612.
  • [15] WU D., TAN D. M., BAIRD M., DECAMPO J., WHITE C., WU H. R. Perceptually lossless medical image coding. IEEE Transactions on Medical Imaging, 2006, Vol. 25. IEEE, pp. 335–344.
  • [16] WU X., MEMON N. CALIC-a context based adaptive lossless image codec. IEEE International Conference on Acoustics, Speech, and Signal Processing, 1996, Vol. 4. pp. 1890–1893.
  • [17] YANG X., LING W., LU Z., ONG E. P., YAO S. Just noticeable distortion model and its applications in video coding. Signal Processing: Image Communication, 2005, Vol. 20. Elsevier, pp. 662–680.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-2d4f9dff-cd19-4d53-9e32-b581b3c7fc60
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