Алгоритмы малоразмерного дискретного косинус-преобразования четвертого типа с уменьшенной мультипликативной сложностью
DOI:
https://doi.org/10.20535/S0021347020090022Ключові слова:
цифровая обработка сигналов, дискретное косинус-преобразование четвертого типа, быстрый алгоритмАнотація
Дискретные косинус-преобразования ДКП широко применяются в интеллектуальных радиоэлектронных системах для обработки и анализа поступающей информации. Популярность использования этих преобразований объясняется наличием быстрых алгоритмов, которые минимизируют вычислительную и аппаратную сложность их реализации. Особое место в перечне преобразований занимает дискретное косинусное преобразование четвертого типа ДКП-IV. В статье предложено несколько алгоритмов реализации ДКП-IV. Эффективность предлагаемых решений обусловлена возможностью факторизации матрицы ДКП-IV, что при реализации ведет к снижению сложности вычислений. В статье также представлен ряд полностью параллельных алгоритмов ДКП-IV для небольших длин N = 2, 3, 4, 5, 6, 7, 8, 9 сигнальных последовательностей.Посилання
- N. Ahmed, T. Natarajan, K. R. Rao, “Discrete cosine transform,” IEEE Trans. Comput., vol. C–23, no. 1, pp. 90–93, 1974, doi: https://doi.org/10.1109/T-C.1974.223784.
- N. Ahmed, K. R. Rao, Orthogonal Transforms for Digital Signal Processing. Berlin, Heidelberg: Springer Berlin Heidelberg, 1975, doi: https://doi.org/10.1007/978-3-642-45450-9.
- K. R. Rao, P. Yip, Discrete Cosine Transform. Elsevier, 1990, doi: https://doi.org/10.1016/C2009-0-22279-3.
- V. Britanak, P. C. Yip, K. R. Rao, Discrete Cosine and Sine Transforms. Elsevier, 2007, doi: https://doi.org/10.1016/B978-0-12-373624-6.X5000-0.
- H. Ochoa-Domínguez, K. R. Rao, Discrete Cosine Transform, 2nd ed. Boca Raton, FL: CRC Press, 2019, doi: https://doi.org/10.1201/9780203729854.
- D. Elliott, K. Rao, Fast Transforms Algorithms, Analyses, Applications, 1st ed. Academic Press, 1983, uri: https://www.elsevier.com/books/fast-transforms-algorithms-analyses-applications/elliott/978-0-08-091806-8.
- B. Chitprasert, K. R. Rao, “Discrete cosine transform filtering,” Signal Process., vol. 19, no. 3, pp. 233–245, 1990, doi: https://doi.org/10.1016/0165-1684(90)90115-F.
- E. Armas Vega, A. Sandoval Orozco, L. García Villalba, J. Hernandez-Castro, “Digital images authentication technique based on dwt, dct and local binary patterns,” Sensors, vol. 18, no. 10, p. 3372, 2018, doi: https://doi.org/10.3390/s18103372.
- L. Krikor, S. Baba, T. Arif, Z. Shaaban, “Image encryption using dct and stream cipher,” Eur. J. Sci. Res., vol. 32, no. 1, pp. 48–58, 2009.
- L. Jing, C. He, L. Zhang, Q. Meng, J. Huang, Q. Zhang, “Iterative block decision feedback equalizer with soft detection for underwater acoustic channels,” Dianzi Yu Xinxi Xuebao/Journal Electron. Inf. Technol., vol. 38, no. 4, pp. 885–891, 2016, doi: https://doi.org/10.11999/JEIT150669.
- J. Yang, T. Jin, C. Xiao, X. Huang, “Compressed sensing radar imaging: fundamentals, challenges, and advances,” Sensors, vol. 19, no. 14, p. 3100, 2019, doi: https://doi.org/10.3390/s19143100.
- C.-F. Lee, J.-J. Shen, Z.-R. Chen, S. Agrawal, “Self-embedding authentication watermarking with effective tampered location detection and high-quality image recovery,” Sensors, vol. 19, no. 10, p. 2267, 2019, doi: https://doi.org/10.3390/s19102267.
- W. Lu et al., “Watermarking based on compressive sensing for digital speech detection and recovery,” Sensors, vol. 18, no. 7, p. 2390, 2018, doi: https://doi.org/10.3390/s18072390.
- K. Boukhechba, H. Wu, R. Bazine, “DCT-based preprocessing approach for ica in hyperspectral data analysis,” Sensors, vol. 18, no. 4, p. 1138, 2018, doi: https://doi.org/10.3390/s18041138.
- P. Xu, B. Chen, L. Xue, J. Zhang, L. Zhu, “A prediction-based spatial-spectral adaptive hyperspectral compressive sensing algorithm,” Sensors, vol. 18, no. 10, p. 3289, 2018, doi: https://doi.org/10.3390/s18103289.
- B.-S. Chow, “Data compression by shape compensation for mobile video sensors,” Sensors, vol. 9, no. 4, pp. 2461–2469, 2009, doi: https://doi.org/10.3390/s90402461.
- P. Christiansen, K. Steen, R. Jørgensen, H. Karstoft, “Automated detection and recognition of wildlife using thermal cameras,” Sensors, vol. 14, no. 8, pp. 13778–13793, 2014, doi: https://doi.org/10.3390/s140813778.
- Z. He, L. Jin, “Activity recognition from acceleration data based on discrete consine transform and svm,” in 2009 IEEE International Conference on Systems, Man and Cybernetics, 2009, pp. 5041–5044, doi: https://doi.org/10.1109/ICSMC.2009.5346042.
- D. C. Swanson, Signal Processing for Intelligent Sensor Systems with MATLAB®, 2nd ed. CRC Press, 2011, doi: http://doi.org/10.1201/b18621.
- Y. A. Reznik, R. K. Chivukula, “Design of fast transforms for high-resolution image and video coding,” in Proceedings of SPIE - The International Society for Optical Engineering, 2009, vol. 7443, p. 744312, doi: https://doi.org/10.1117/12.831216.
- V. Britanak, K. R. Rao, Cosine-/Sine-Modulated Filter Banks. Cham: Springer International Publishing, 2018, doi: https://doi.org/10.1007/978-3-319-61080-1.
- T. D. Tran, J. Liang, T. Chengjie, “Lapped transform via time-domain pre- and post-filtering,” IEEE Trans. Signal Process., vol. 51, no. 6, pp. 1557–1571, 2003, doi: https://doi.org/10.1109/TSP.2003.811222.
- A. K. Jain, “A sinusoidal family of unitary transforms,” IEEE Trans. Pattern Anal. Mach. Intell., vol. PAMI-1, no. 4, pp. 356–365, 1979, doi: https://doi.org/10.1109/TPAMI.1979.4766944.
- N. R. Murthy, M. N. S. Swamy, “On the on-line computation of dct-iv and dst-iv transforms,” IEEE Trans. Signal Process., vol. 43, no. 5, pp. 1249–1251, 1995, doi: https://doi.org/10.1109/78.382409.
- Z. C. Li, “On computing the two-dimensional (2-d) type iv discrete cosine transform (2-d dct-iv),” IEEE Signal Process. Lett., vol. 8, no. 8, pp. 239–241, 2001, doi: https://doi.org/10.1109/97.935741.
- Y. Zeng, Z. Lin, G. Bi, L. Cheng, “Fast computation of md-dct-iv/md-dst-iv by md-dwt or md-dct-ii,” SIAM J. Sci. Comput., vol. 24, no. 6, pp. 1903–1918, 2003, doi: https://doi.org/10.1137/S1064827501394830.
- H.-W. Hsu, C.-M. Liu, “Fast radix-q and mixed-radix algorithms for type-iv dct,” IEEE Signal Process. Lett., vol. 15, pp. 910–913, 2008, doi: https://doi.org/10.1109/LSP.2008.2005441.
- X. Dai, M. Wagh, “Bilinear algorithms and vlsi implementations of forward and inverse mdct with applications to mp3 audio,” WO/2009/100021, 13-Aug-2009.
- V. Britanak, “Comments on fast radix-9 algorithm for the dct-iv computation,” IEEE Signal Process. Lett., vol. 16, no. 11, pp. 1005–1006, 2009, doi: https://doi.org/10.1109/LSP.2009.2028450.
- X. Shao, S. G. Johnson, “Type-iv dct, dst, and mdct algorithms with reduced numbers of arithmetic operations,” Signal Process., vol. 88, no. 6, pp. 1313–1326, 2008, doi: https://doi.org/10.1016/j.sigpro.2007.11.024.
- V. Britanak, “The fast dct-iv/dst-iv computation via the mdct,” Signal Process., vol. 83, no. 8, pp. 1803–1813, 2003, doi: https://doi.org/10.1016/S0165-1684(03)00109-9.
- A. M. Grigoryan, M. M. Grigoryan, “A novel algorithm of the 4-point type-iv discrete cosine transform,” 2008.
- V. S. Shaptala, M. V. Korman, “DCT-iv computation,” Pattern Recognit. Image Anal., vol. 18, no. 1, pp. 58–62, 2008, doi: https://doi.org/10.1134/S1054661808010070.
- S. M. Perera, “Signal processing based on stable radix-2 dct i-iv algorithms having orthogonal factors,” Electron. J. Linear Algebr., vol. 31, no. 1, pp. 362–380, 2016, doi: https://doi.org/10.13001/1081-3810.3207.
- X. Dai, M. D. Wagh, “An mdct hardware accelerator for mp3 audio,” in 2008 Symposium on Application Specific Processors, 2008, pp. 121–125, doi: https://doi.org/10.1109/SASP.2008.4570796.
- D. Chiper, “A new vlsi algorithm and architecture for the hardware implementation of type iv discrete cosine transform using a pseudo-band correlation structure,” Open Comput. Sci., vol. 1, no. 2, pp. 243–250, 2011, doi: https://doi.org/10.2478/s13537-011-0015-z.
- M. Garrido, O. Gustafsson, F. Qureshi, “Unified architecture for 2, 3, 4, 5, and 7-point dfts based on winograd fourier transform algorithm,” Electron. Lett., vol. 49, no. 5, pp. 348–349, 2013, doi: https://doi.org/10.1049/el.2012.0577.
- H. M. de Oliveira, R. J. Cintra, R. M. C. de Souza, “A factorization scheme for some discrete hartley transform matrices,” 2015, uri: http://arxiv.org/abs/1502.01038.
- А. П. Царёв, М. Маковска, П. Стшелец, “Алгоритмы прямого и обратного ДКП малых порядков с уменьшенной мультипликативной сложностью,” Известия вузов. Радиоэлектроника, vol. 62, no. 11, pp. 662–677, 2019, doi: https://doi.org/10.20535/S0021347019110025.
- A. Cariow, J. Papliński, D. Majorkowska-Mech, “Some structures of parallel vlsi-oriented processing units for implementation of small size discrete fractional fourier transforms,” Electronics, vol. 8, no. 5, p. 509, 2019, doi: https://doi.org/10.3390/electronics8050509.
- A. Ţariov, D. Majorkowska-Mech, “The multilevel signal representation in discrete base of cosine functions,” Elektronika, vol. 48, no. 7, pp. 20–21, 2007.
- A. Ţariov, Algorithmic Aspects of Computing Rationalization in Digital Signal Processing. Szczecin: West Pomeranian University Press, 2012.
- A. Cariow, “Strategies for the synthesis of fast algorithms for the computation of the matrix-vector products,” J. Signal Process. Theory Appl., no. 3, pp. 1–19, 2014, doi: https://doi.org/10.7726/jspta.2014.1001.
- J. Granata, M. Conner, R. Tolimieri, “The tensor product: a mathematical programming language for ffts and other fast dsp operations,” IEEE Signal Process. Mag., vol. 9, no. 1, pp. 40–48, 1992, doi: https://doi.org/10.1109/79.109206.
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Опубліковано
2020-09-22
Як цитувати
Царёв, А. П., & Лесецки, Л. (2020). Алгоритмы малоразмерного дискретного косинус-преобразования четвертого типа с уменьшенной мультипликативной сложностью. Вісті вищих учбових закладів. Радіоелектроніка, 63(9), 549–569. https://doi.org/10.20535/S0021347020090022
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