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Gradient flow optimization for reducing blocking effects of transform coding

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
This paper addresses the problem of reducing blocking effects in transform coding. A novel optimization approach using the gradient flow is proposed. Using some properties of the gradient flow on a manifold, an optimized filter design method for reducing the blocking effects is presented. Based on this method, an image reconstruction algorithm is derived. The algorithm maintains the fidelity of images while reducing the blocking effects. Experimental tests demonstrate that the presented algorithm is effective.
Rocznik
Strony
105--111
Opis fizyczny
Bibliogr. 13 poz., rys.
Twórcy
autor
  • Department of Electrical and Computer Engineering and Computer Science, University of Cincinnati
autor
  • Department of Electrical and Computer Engineering and Computer Science, University of Cincinnati
autor
  • Department of Electrical and Computer Engineering and Computer Science, University of Cincinnati
autor
  • Department of Electrical and Computer Engineering and Computer Science, University of Cincinnati
Bibliografia
  • [1] Helmke U. and Moore J.B. (1994): Optimization and Dynamical Systems.—London: Springer-Verlag.
  • [2] ISO (1991) : Commitee Draft ISO/IEC CD 10918-1, Digital compression and coding of continuous-tone still images, Part 1: Requirements and guidelines, March 15, 1991.
  • [3] ISO (1993): ISO/IEC JTC1/SC29/WG11, Test Models 5, MPEG 93/457, Document AVC-491, April,1993.
  • [4] Jain A.K. (1989): Fundamentals of Digital Image Processing. —Englewood Cliffs, NJ: Prentice-Hall.
  • [5] Kim T.K., Paik J.K.,Won C.S., Choe Y.S., Jeong J. and Nam J.Y. (2000): Blocking effect reduction of compressed images using classification-based constrained optimization.—Sign. Process. Image Comm., Vol. 15, pp. 869–877.
  • [6] Minami S. and Zakhor A. (1995): An optimization approach for removing blocking effects in transform coding. — IEEE Trans. Circ. Syst. [Video Technol]., Vol. 5, No. 2, pp. 74–82.
  • [7] Rao K.K. and Hwang J.J. (1996), Techniques and Standards for Image, Video and Audio Coding.—Englewood Cliffs, NJ: Prentice Hall, Inc.
  • [8] Rapcsak T. (1997), Smooth Nonlinear Optimization in Rn. — Dordrecht: Kluwer.
  • [9] Reeve H.C. and Lim J.S. (1984): Reduction of blocking effects in image coding.—Opt. Eng., Vol. 23, No. 1, pp. 34–37.
  • [10] Rosenholtz R. and Zakhor A. (1992): Iterative procedures for reduction of blocking effects in transform image coding. — IEEE Trans. Circ. Syst. Video Technol., Vol. 2, No. 1, pp. 91–94.
  • [11] Won C.S. and Derin H. (1992): Unsupervised segmentation of noisy and textured images using Markov random fields. — CVGIP: Graph. Mod. Image Process., Vol. 54, No. 4, pp. 308–328.
  • [12] Yang Y., Galatsanos N.P. and Katsaggelos A.K. (1993): Regularized reconstruction to reduce blocking artifacts of block discrete cosine transform compressed images. — IEEE Trans. Circ. Syst. [Video Technol]., Vol. 3, No. 6, pp. 421–432.
  • [13] Yang Y., Galatsanos N.P. and Katsaggelos A.K. (1995): Projection-based spatially adaptive reconstruction of block-transform compressed images. — IEEE Trans. Image Process., Vol. 4, No. 7, pp. 896–908.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BPZ1-0007-0012
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