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Supercompression for Full-HD and 4k-3D (8k)Digital TV Systems

Authors: Mario Mastriani


In this work, we developed the concept of supercompression, i.e., compression above the compression standard used. In this context, both compression rates are multiplied. In fact, supercompression is based on super-resolution. That is to say, supercompression is a data compression technique that superpose spatial image compression on top of bit-per-pixel compression to achieve very high compression ratios. If the compression ratio is very high, then we use a convolutive mask inside decoder that restores the edges, eliminating the blur. Finally, both, the encoder and the complete decoder are implemented on General-Purpose computation on Graphics Processing Units (GPGPU) cards. Specifically, the mentio-ned mask is coded inside texture memory of a GPGPU.

Keywords: Image Compression, Super-resolution, Interpolation, General-Purpose computation on Graphics Processing Units

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[1] M. Mastriani, "Single Frame Supercompression of Still Images, Video, High Definition TV and Digital Cinema", International Journal of Information and Mathematical Sciences, vol. 6:3, pp. 143-159, 2010.
[2] A. Gilman, D. G. Bailey, S. R. Marsland, "Interpolation Models for Image Super-resolution," in Proc. 4th IEEE International Symposium on Electronic Design, Test & Applications, DELTA 2008, Hong Kong, 2008, pp.55-60.
[3] D. Glassner, S. Bagon, M. Irani. Super-Resolution from a Single Image. Available: e_image_SR.pdf
[4] A. Lukin, A. S. Krylov, A. Nasonov. Image Interpolation by Super- Resolution. Available:
[5] Y. Huang, "Wavelet-based image interpolation using multilayer perceptrons," Neural Comput. & Applic., vol.14, pp.1-10, 2005.
[6] N. Mueller, Y. Lu, and M. N. Do. Image interpolation using multiscale geometric representations. Avalilable:
[7] S.H.M. Allon, M.G. Debertrand, and B.T.H.M. Sleutjes, "Fast Deblurring Algorithms", 2004. Available: 3.2bDeblur/OGO3.2b_2004_Deblur.pdf
[8] A. Bennia and S.M. Riad, Filtering Capabilities and Convergence of the Van-Cittert Deconvolution Technique, IEEE, Trans. Instrum. Meas., Vol. 41, no. 2, pp. 246-250, Apr. 1992.
[9] M. Kraus, M. Eissele, and M. Strengert. GPU-Based Edge-Directed Image Interpolation. Available:
[10] -. NVIDIA CUDA: Best Practices Guide, version 3.0, 2/4/2010. Available: VIDIA_CUDA_BestPracticesGuide.pdf
[11] V. Podlozhnyuk. Image Convolution with CUDA, June 2007. Available: ts/convolutionSeparable/doc/convolutionSeparable.pdf
[12] V. Simek, and R. Rakesh, "GPU Acceleration of 2D-DWT Image Compression in MATLAB with CUDA," in Proc. Second UKSIM European Symposium on Computer Modeling and Simulations, Liverpool, UK, 2008, pp.274-277.
[13] R.C. Gonzalez, R.E. Woods, Digital Image Processing, 2nd Edition, Prentice- Hall, Jan. 2002, pp.675-683.
[14] A.K. Jain, Fundamentals of Digital Image Processing, Englewood Cliffs, New Jersey, 1989.
[15] I. E. Richardson, H.264 and MPEG-4 Video Compression: Video Coding for Next Generation Multimedia, Ed. Wiley, N.Y., 2003.
[18] NVIDIA® (NVIDIA Corporation, Santa Clara, CA).
[20] J. Miano, Compressed Image File Formats: JPEG, PNG, GIF, XBM, BMP; Ed. Addison-Wesley, N.Y., 1999.
[21] T. Acharya, and P-S Tsai, JPEG2000 Standard for Image Compression: Concepts, Algorithms and VLSI Architectures, Ed. Wiley, N.Y., 2005.
[22] A. Bilgin, and M. W. Marcellin, "JPEG2000 for Digital Cinema" in Proceedings of 2006 International Symposium on Circuits and Systems (ISCAS), (invited paper), May 2006.
[23] MATLAB® R2010b (Mathworks, Natick, MA).