Reversible image watermarking technique using LCWT and DGT

 
 
 
  • Abstract
  • Keywords
  • References
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  • Abstract


    In this contemporary world procuring our confidential data against some unknown person is very significant. Thus to have a high reliability of data security watermarking technique is applied before transmitting the data. This proposed work LCWT and DGT decomposition gives an effective technique to protect hypertensive related information based on reversible watermarking. LCWT has the superiority of multi-resolution fundamental analysis of wavelet transform and reflects representation of image domain in LCT. And using DGT decomposition the patient information has to embed inside high frequency subband wavelet and the watermarked information will be extracted by the receiver without any loss, to reconstruct the original image information. The reliability of the proposed method is analyzed by comparing the experimental results of similarity index, normalization and peak signal to noise ratio.


  • Keywords


    DGT; LCWT; PSNR; Normalization; Watermarking

  • References


      [1] Sivakannan, S, Thirugnanam, G and Mangaiyarkarasi, P,(2017), Implementation of Medical Image Watermarking Technique using FPGA, Communications in Computer and Information Science, Advances in computing and data sciences, pp. 149-157

      [2] Yong Guo, Bing-Zhao Li. ‘Blind image watermarking method based on linear canonical wavelet transform and QR decomposition’, The Institute of Engineering and Technology, 2016, 10(10), 773 – 786.

      [3] Priya S., Santhi B., et al.: ‘Hybrid Transform Based Reversible Watermarking Technique for Medical Images in Telemedicine Applications’, Optik - International Journal for Light and Electron Optics, 145, 655-671.

      [4] Das, S., Kundu, M. K, Effective management of medical information through a novel blind watermarking technique. Journal of Medical Systems,36(5), 2012, 3339–3351. doi: 0.1007/s10916-012-9827-1.

      [5] Giakoumaki, A,Pavlopoulos, S, Koutsouris D, Multiple image watermarking applied to health information management. IEEE Transactions on Information Technology in Biomedicine, 10(4), 2006,722–732. doi:10.1109/TITB.2006.875655.

      [6] Huang C L, Tseng L Y, Hwang M S, A reversible data hiding method by histogram shifting in high quality medical images, Journal of systems and software, 86(3), 2013, 716–727 .doi:10.1016/j.jss.2012.11.024.

      [7] ThabitR,Khoo B E, Robust reversible watermarking scheme using Slantlet transform matrix, Journal of systems and software, 88,2014, 74-86. doi:10.1016/j.jss.2013.09.033

      [8] ThabitR,Khoo B E, A new robust lossless data hiding scheme and its application to color medical images.38,2015, 77–94, doi:10.1016/j.dsp.2014.12.005.

      [9] RashaThabit, Bee EeKhoo, Robust reversible watermarking scheme using Slantlet transform matrix. The Journal of Systems and Software 88,2014, 74– 86. doi:10.1016/j.jss.2013.09.033.

      [10] Le H M, Aburdene M, The discrete Gould transform and its applications, Proc. of SPIE Image Processing: Algorithms and Systems, Neural Networks, and Machine Learning, Vol. 606401,2006,1-12.doi: 10.1117/12.643278

      [11] Varsaki E, Fotopoulos V, Skodras A N, A discrete Gould transform data hiding scheme, Mathematical .Methods in the Applied Sciences,37(2), 2014, 283–288. doi: 10.1002/mma.3041

      [12] Skodras A N, The discrete Gould Transform -Fast realisations and data hiding, Constantinides International workshop on Signal Processing doi:10.1049/ic.2013.0003.

      [13] Ni, Z., Shi, Y.Q., Ansari, N., Su, W., Sun, Q., Lin, X, Robust lossless image data hid-ing designed for semi- fragile image authentication. IEEE Transactions on Circuits and Systems for Video Technology 18 (4), 2008, 97–509. doi:10.1109/TCSVT.2008.918761.

      [14] Koc, A., Ozaktas, H.M., Candan, C., et al.: ‘Digital computation of linear canonical transforms’, IEEE Trans. Signal Process., 2008, 56, (6), pp. 2383–2394

      [15] Healy, J.J., Sheridan, J.T.: ‘Sampling and discretization of the linear canonical transform’, Signal Process., 2009, 89, (4), pp. 641–648

      [16] Li, Y.G., Li, B.Z., Sun, H.F.: ‘Uncertainty principles for Wigner-Ville distribution associated with the linear canonical transforms’, Abs. Appl. Anal., 2014, 2014, pp. 1–9

      [17] Shi, J., Liu, X., Zhang, N.T.: ‘Generalized convolution and product theorems associated with linear canonical transform’, Signal Image Video Process., 2014, 8, (5), pp. 967–974

      [18] Shi, J., Sha, X., Zhang, Q., et al.: ‘Extrapolation of bandlimited signals in linear canonical transform domain’, IEEE Trans. Signal Process., 2012, 60, (3), pp. 1502–1508

      [19] Xu, T.Z., Li, B.Z.: ‘Linear canonical transform and its application’ (Science Press, Beijing, 2013)

      Wei, D., Li, Y.M.: ‘Generalized wavelet transform based on the convolution operator in the linear canonical transform domain’, Optik-Int. J. Light Electron Opt., 2014, 125, (16), pp. 4491–4496

 

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Article ID: 9224
 
DOI: 10.14419/ijet.v7i1.3.9224




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