A mathematical theory of communication

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  1. C.E.Shannon, “A Mathematical theory of communication”, The Bell System Technical Journal, Vol.27, pp. 379-423, 1948.

  2. Nyquist. H., “Certain topics in Telegraphic Transmission theory”, A.I.E.E Trans. pp.617 -644, 1928.

  3. Weinberger, M. J., Seroussi, G., and Sapiro, G. “LOCO-I: A low complexity, context-based, lossless image compression algorithm”,. IEEE conference on Data Compression (IEEE - DCC'96), pp. 140-149, 1996.

  4. Mandyam, G., Ahmed, N., and Magotra, N. “Lossless image compression using the discrete cosine transform”, Journal of Visual Communication and Image Representation, Vol.8, No.1, pp.21-26, 1997.

  5. Calderbank, A. R., Daubechies, I., Sweldens, W., and Yeo, B. L. “Lossless image compression using integer to integer wavelet transforms”. IEEE International Conference on Image Processing, Vol. 1, pp. 596-599, 1997.

  6. Wu, X., and Memon, N., “Context-based, adaptive, lossless image coding”, IEEE Transactions on Communications, Vol. 45, No.4, pp. 437-444, 1997.

  7. Boulgouris, N. V., Tzovaras, D., and Strintzis, M. G. “Lossless image compression based on optimal prediction, adaptive lifting, and conditional arithmetic coding”, IEEE Transactions on Image Processing, Vol.10, No.1, pp.1-14, 2001.

  8. Pan, H., Siu, W. C., and Law, N. F., “Lossless image compression using binary wavelet transform”, IET Image Processing, Vol.1, No.4, pp.353-362, 2007.

  9. Zhao, X. O., and He, Z. H., “Lossless image compression using super-spatial structure prediction”, IEEE Signal Processing Letters, Vol.17,No.4, pp.383-386, 2010.

  10. Yerva, S., Nair, S., and Kutty, K., “Lossless image compression based on data folding”,IEEE International Conference on Recent Trends in Information Technology (ICRTIT- 2011), pp. 999-1004, 2011.

  11. Koc, B., Arnavut, Z., Kocak, H., “Lossless Compression of Dithered Images,” IEEE Photonics Journal, , vol.5, no.3, pp. 508-517, 2013.

  12. Delp, E., and Mitchell, O. “Image compression using block truncation coding”, IEEE Transactions on Communications, Vol.27 ,No.9,pp. 1335-1342 , 1979.

  13. J.M.Shapiro., “ Embedded image coding using zero-tress of wavelet coefficients”, IEEE Transactions on Signal Processing , Vol.41, pp. 3445-3462, 1993.

  14. Said, A., and Pearlman, W. A. “A new, fast, and efficient image codec based on set partitioning in hierarchical trees”, IEEE Transactions on Circuits and Systems for Video Technology, Vol. 6 No.3, pp. 243-250, 1996.

  15. Taubman, D. “High performance scalable image compression with EBCOT”, IEEE transactions on Image Processing, Vol. 9, No.7, pp.1158-1170, 2000.

  16. Wallace, G. K, “The JPEG still picture compression standard”, IEEE Transactions on Consumer Electronics, Vol.38, No.1, pp. xviii-xxxiv, 1992.

  17. Dony, R. D., and Haykin, S. “Neural network approaches to image compression”, Proceedings of the IEEE, 83(2), 288-303. 1995.

  18. Delp, E. J., Salama, P., Asbun, E., Saenz, N., and Shen, K., “Rate scalable image and video compression techniques”, 42nd Midwest IEEE Symposium on Circuits and Systems, Vol. 2, pp. 635-638, 1999

  19. Jiang, J., “Image compression with neural networks–a survey”. Signal Processing: Image Communication, Vol.14, No.9, pp. 737-760, 1999.

  20. Antonini, M., Barlaud, M., Mathieu, P., and Daubechies, I.“Image coding using wavelet transform”, IEEE Transactions on Image Processing, Vol.1, No.2, pp. 205-220, 1992.

  21. Averbuch, A., Lazar, D., and Israeli, M., “Image compression using wavelet transform and multi resolution decomposition”, IEEE Transactions on Image Processing, Vol.5, No.1, pp. 4-15, 1996.

  22. Buccigrossi, R. W., and Simoncelli, E. P., “Image compression via joint statistical characterization in the wavelet domain”, IEEE Transactions on Image Processing, Vol.8, No.12, pp.1688-1701, 1999.

  23. Bilgin, A., Zweig, G., and Marcellin, M. W., “ Three-dimensional image compression with integer wavelet transforms”, Applied optics, Vol.39, No.11, pp.1799-1814, 2000.

  24. Skodras, A., Christopoulos, C., and Ebrahimi, T., “The JPEG 2000 still image compression standard”, IEEE Signal Processing Magazine, Vol.18, No.5, pp. 36-58, 2001.

  25. O'Leary, D., and Peleg, S., “ Digital image compression by outer product expansion”, IEEE Transactions on Communications, Vol.31, No.3, pp.441-444, 1983

  26. Seung, D., and Lee, L., “Algorithms for non-negative matrix factorization”, Advances in neural information processing systems, Vol.13, pp. 556-562, 2001

  27. Costa, S., and Fiori, S., “Image compression using principal component neural networks”, Image and Vision Computing, Vol.19, No.9, pp.649-668, 2001.

  28. Hao, P.,and Shi, Q., “Matrix factorizations for reversible integer mapping”, IEEE Transactions on Signal Processing, Vol.49, No.10, pp.2314-2324, 2001.

  29. Ferreira, A. J., and Figueiredo, M. A., “Image compression using orthogonalized independent components bases”, IEEE 13th Workshop on Neural Networks for Signal Processing,.( NNSP'03) , pp. 689-698, 2003.

  30. Yuan, Z., and Oja, E., “Projective nonnegative matrix factorization for image compression and feature extraction”, Image Analysis (pp. 333-342). Springer Berlin Heidelberg. 2005.

  31. Hazan, T., Polak, S., and Shashua, A., “Sparse image coding using a 3D non-negative tensor factorization”, Tenth IEEE International Conference on Computer Vision, (ICCV 2005), Vol. 1, pp. 50-57, 2005.

  32. Luigi Dragotti, P., Poggi, G., and Ragozini, A. R., “Compression of multispectral images by three-dimensional SPIHT algorithm”, IEEE Transactions on Geoscience and Remote Sensing, Vol. 38, No.1, pp. 416-428, 2000.

  33. Tang, X., Pearlman, W. A., and Modestino, J. W., “Hyper spectral image compression using three-dimensional wavelet coding”, Electronic Imaging-2003, International Society for Optics and Photonics, pp. 1037-1047, 2003.

  34. Wang, J., and Chang, C. I., “Independent component analysis-based dimensionality reduction with applications in hyper spectral image analysis”, IEEE Transactions on Geo science and Remote Sensing, Vol. 44, No.6, pp.1586-1600, 2006.

  35. Ramakrishna, B., Plaza, A. J., Chang, C. I., Ren, H., Du, Q., and Chang, C. C, “Spectral/spatial hyper spectral image compression”, Hyper spectral data compression pp. 309-346, Springer US. 2006.

  36. Du, Q., and Fowler, J. E., “Hyper spectral image compression using JPEG2000 and principal component analysis”, IEEE Geoscience and Remote Sensing Letters, Vol. 4, No.2, pp.201-205, 2007.

  37. Penna, B., Tillo, T., Magli, E., and Olmo, G., “Transform coding techniques for lossy hyperspectral data compression”, IEEE Transactions on Geo science and Remote Sensing, Vol.45, No.5, pp.1408-1421, 2007.

  38. Wang, H., Babacan, S. D., and Sayood, K., “Lossless hyperspectral-image compression using context-based conditional average”, IEEE Transactions on Geo science and Remote Sensing, Vol. 45, No.12, pp.4187-4193, 2007.

  39. Christophe, E., Mailhes, C., and Duhamel, P., “Hyper spectral image compression: adapting SPIHT and EZW to anisotropic 3-D wavelet coding”, IEEE Transactions on Image Processing, Vol.17, No.12, pp.2334-2346, 2008.

  40. Du, Q., and Fowler, J. E., “Low-complexity principal component analysis for hyper spectral image compression”, International Journal of High Performance Computing Applications, Vol.22, No.4, pp.438-448, 2008.

  41. Magli, E., “Multiband lossless compression of hyperspectral images”, IEEE Transactions on Geoscience and Remote Sensing, Vol.47, No.4, pp.1168-1178, 2009.

  42. Abrardo, A., Barni, M., Magli, E., and Nencini, F., “Error-resilient and low-complexity onboard lossless compression of hyperspectral images by means of distributed source coding”, IEEE Transactions on Geoscience and Remote Sensing, Vol.48, No.4, pp.1892-1904, 2010.

  43. Karami, A., Yazdi, M., and Mercier, G., “Compression of hyperspectral images using discerete wavelet transform and Tucker decomposition”, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol.5, No.2, pp. 444-450. 2012.

  44. Burlina, P., and Alajaji, F., “An error resilient scheme for image transmission over noisy channels with memory”, IEEE Transactions on Image Processing, Vol.7, No.4, pp. 593-600, 1998.

  45. Kozintsev, I., Chou, J., and Ramchandran, K., “Image transmission using arithmetic coding based continuous error detection”, IEEE Data Compression Conference, -DCC'98., pp. 339-348, 1998.

  46. Chou, J., and Ramchandran, K., “Arithmetic coding-based continuous error detection for efficient ARQ-based image transmission”, IEEE Journal on Selected Areas in Communications, Vol.18, No.6, pp.861-867, 2000.

  47. Cosman, P. C., Rogers, J. K., Sherwood, P. G., and Zeger, K., “Combined forward error control and packetized zerotree wavelet encoding for transmission of images over varying channels”, IEEE Transactions on Image Processing, Vol.9, No.6, pp.982-993, 2000.

  48. Chande, V., and Farvardin, N., “Progressive transmission of images over memoryless noisy channels”, IEEE Journal on Selected Areas in Communications, Vol.18, No.6, pp.850-860, 2000.

  49. Anand, R., Ramchandran, K., and Kozintsev, I. V., “Continuous error detection (CED) for reliable communication”, IEEE Transactions on Communications, Vol.49, No.9, pp.1540-1549, 2001.

  50. Song, J., and Liu, K. R., “Robust progressive image transmission over OFDM systems using space-time block code”, IEEE Transactions on Multimedia, Vol.4, No.3,pp. 394-406, 2002.

  51. Gabay, A., Kieffer, M., and Duhamel, P., “Joint source-channel coding using real BCH codes for robust image transmission”, IEEE Transactions on Image Processing, Vol. 16, No.6, pp.1568-1583, 2007.

  52. Baruffa, G., Micanti, P., and Frescura, F., “Error protection and interleaving for wireless transmission of JPEG 2000 images and video”, IEEE Transactions on Image Processing,Vol.18, No.2, pp. 346-356, 2009.

  53. Arslan, S. S., Cosman, P. C., and Milstein, L. B., “Generalized unequal error protection LT Codes for progressive data transmission”, IEEE Transactions on Image Processing, Vol. 21, No.8, 3586-3597, 2012.

  54. El-Bakary, E. M., Hassan, E. S., Zahran, O., El-Dolil, S. A., and El-Samie, F. A., “Efficient Image Transmission with Multi-Carrier CDMA”, Wireless Personal Communications, pp.1-16. 2013.

  55. Rafel.C. Gonzalez and Richard.E. Woods., “Digital Image Processing”, 3rd edition,Pearson publication, 2008.(online image database).

  56. Strang, G., “Wavelets and dilation equations: A brief introduction”, SIAM review, Vol.31, No.4, pp.614-627, 1989.

  57. Foster, D.H., Amano,K., Nascimento,S.M.C., and Foster,M.j., “ Frequency of metamerism in natural scenes”, Journal of the optical society of America- A, Vol 23, pp.no 2359-2372, 2006.

  58. Theodore.S.Rappaport, “ Wireless Communications . Principles and Practices ”, 2nd edition, Pearson publication, pp 210-214, 2009.

  59. Bernard.Sklar, “ Digital Communication: Fundamentals & Applications”, 2nd edition, Pearson education India, pp. 210-235, 2009.

  60. Johnson.H., Graham.M., “High-speed signal propagation – Advanced black magic”, Prentice-Hall PTR, pp-363-438, 2002.


  1. Perumalsamy. N.(Nallathai) and Natarajan .N(Nithiyanandam), “A non-iterative method for factorization of positive matrix in discrete wavelet transform based image compression”. American Journal of Applied Sciences.,Vol. 10, pp.664-668, 2013.

  1. Nallathai.P, Jeyakumar.S and Nithiyanandam.N., “Hyper spectral image compression based on non-iterative matrix factorization” , Proceedings of IEEE International Conference on Computational Intelligence and Computing Research (ICCIC 2013), Vol.1. pp. 528-531, 2013. (ISBN -978-1-4799-1597-2).


  1. Nallathai.P, and Nithiyanandam.N “Development of a differential signaling based BPSK transmission system and its performance in AWGN, Rayleigh and Rician channels”, IET Communications.

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