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Hardware-Efficient Schemes of Quaternion Multiplying Units for 2D Discrete Quaternion Fourier Transform Processors

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
In this paper, we offer and discuss three efficient structural solutions for the hardware-oriented implementation of discrete quaternion Fourier transform basic operations with reduced implementation complexities. The first solution – a scheme for calculating sq product, the second solution – a scheme for calculating qt product, and the third solution – a scheme for calculating sqt product, where s is a so-called i -quaternion, t is an j - quaternion, and q – is an usual quaternion. The direct multiplication of two usual quaternions requires 16 real multiplications (or two-operand multipliers in the case of fully parallel hardware implementation) and 12 real additions (or binary adders). At the same time, our solutions allow to design the computation units, which consume only 6 multipliers plus 6 two input adders for implementation of sq or qt basic operations and 9 binary multipliers plus 6 two-input adders and 4 four-input adders for implementation of sqt basic operation.
Wydawca
Rocznik
Strony
206--208
Opis fizyczny
Bibliogr. 17 poz., rys., wzory
Twórcy
autor
  • West Pomieranian University of Technology, 49 Żołnierska St., 71-210 Szczecin, Poland
autor
  • West Pomieranian University of Technology, 49 Żołnierska St., 71-210 Szczecin, Poland
autor
  • Samara University, 34 Moskovskoye sh., 443086 Samara, Russia
  • IPSI RAS – Branch of the FSRC “Crystallography and Photonics”, 151, 443001 Samara, Russia
Bibliografia
  • [1] Pratt W. K.: Digital Image Processing, Part III, Chapter 8, pp. 185-212 3rd Edition, John Wiley & Sons, Inc. 2001. ISBNs: 0-471-37407-5.
  • [2] Sangwine S. J.: Fourier transforms of color images using quaternion or hypercomplex numbers, Electronics Letters, Vol. 32, No. 21, 10 Oct 1996 ), Page(s): 197–198 DOI: 10.1049/el:19961331.
  • [3] Sangwine S. J.: The discrete quaternion Fourier transform. 6th International Conference on Image Processing and its Applications. 1997, p. 790–793, DOI: 10.1049/cp:19971004.
  • [4] Ell T. A., Sangwine S. J.: Decomposition of 2D hypercomplex Fourier transforms into pairs of complex Fourier transforms. In: Moncef Gabbouj and Pauli Kuosmanen, editors, Proceedings of EUSIPCO 2000, Tenth European Signal Processing Conference, volume II, pages 1061–1064. Tampere, Finland, 5–8 September 2000. European Association for Signal Processing.
  • [5] Bülow T. and Sommer G.: Hypercomplex signals - a novel extension of the analytic signal to the multidimensional case. IEEE Trans. Sign. Proc., vol. SP-49, no. 11, pp. 2844–2852, Nov. 2001.
  • [6] Schütte H.-D. and Wenzel J.: Hypercomplex numbers in digital signal processing. In Proc. ISCAS ’90, New Orleans, 1990, pp. 1557–1560.
  • [7] Alfsmann D.: On families of 2N-dimensional hypercomplex algebras suitable for digital signal processing. In Proc. European Signal Processing Conf. (EUSIPCO 2006), Florence, Italy, 2006.
  • [8] Alfsmann D., Göckler H. G., Sangwine S. J. and Ell T. A.: Hypercomplex Algebras in Digital Signal Processing: Benefits and Drawbacks (Tutorial). Proc. EURASIP 15th European Signal Processing Conference (EUSIPCO 2007), Poznań, Poland, 2007, pp. 1322-1326.
  • [9] Sangwine S. J., Bihan N. Le: Hypercomplex analytic signals: extension of the analytic signal concept to complex signals. Proc. EURASIP 15th European Signal Processing Conference (EUSIPCO 2007), Poznań, Poland, 2007, Poznań, pp. 621-624.
  • [10] Pei S.-Ch., Ding J.-J., Chang J.-H.: Efficient implementation of quaternion Fourier transform, convolution, and correlation by 2-D complex FFT, IEEE Transactions on Signal Processing, 2001, Vol. 49, No. 11, pp. 2783-2797.
  • [11] Ell T. A., Sangwine S. J.: Hypercomplex Fourier Transforms of Color Images. IEEE Transactions on Image Processing, 2007, Vol. 16, No. 1, pp. 22-35.
  • [12] Felsberg M. and Sommer G.: Optimized fast algorithms for the quaternionic Fourier transform. In: F. Solina and A. Leonardis, editors, Computer Analysis of Images and Patterns. Vol. 1689 of Lecture Notes in Computer Science, pp. 209–216. Springer, 1999. 8th International Conference CAIP’99, Ljubljana, September 1–3, 1999 Proceedings.
  • [13] Said S., Le Bihan N., Sangwine S. J.: Fast complexified quaternion Fourier transform. IEEE Transactions on Signal Processing 2008, Vol. 56, No. 4, pp. 1522-1531.
  • [14] Chichyeva M. A., Pershina M. V.: On various schemes of 2D-DFT decomposition with data representation in the quaternion algebra. Image Processing and Communications, Institute of Telecommunications, Bydgoszcz, Poland, vol. 2, No. 1, pp. 13-20, 1996.
  • [15] Ţariova G., Ţariov A.: Aspekty algorytmiczne redukcji liczby bloków mnożących w układzie do obliczania iloczynu dwóch kwaternionów. Pomiary Automatyka Kontrola, No. 7, 2010, pp. 668-690.
  • [16] Parfieniuk M., Park S. Y.: Sparse-iteration 4D CODRIC Algorithms for multiplying quaternions. IEEE Transaction on Computers, 2016, v. 65, no. 9, pp. 2859-2871.
  • [17] Cariow A.: Strategies for the Synthesis of Fast Algorithms for the Computation of the Matrix-vector Products. Journal of Signal Processing Theory and Applications, 2014, v. 3, No. 1, pp. 1-19.
Uwagi
PL
Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę (zadania 2017).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-f958ed39-e3d1-418e-8eaa-0d4479b60a69
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