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Open AccessArticle

Low-Complexity Loeffler DCT Approximations for Image and Video Coding

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Independent Researcher, Calgary AB, T3A 2H6, Canada
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Department of Electrical and Computer Engineering, University of Calgary, 2500 University Dr. NW Calgary, AB T2N 1N4, Canada
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Signal Processing Group, Departamento de Estatística, Universidade Federal de Pernambuco, Recife 50670-901, PE, Brazil
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Departamento de Estatística and LACESM, Universidade Federal de Santa Maria, Santa Maria 97105-900, RS, Brazil
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Department of Electrical and Computer Engineering, University of Akron, Akron, OH 44325, USA
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Department of Electrical and Computer Engineering, Florida International University, Miami, FL 33174, USA
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Friedrich-Alexander-Universität Erlangen-Nürnberg, 91054 Erlangen, Germany
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Programa de Pós-Graduação em Computação, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre 91501-970, RS, Brazil
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Programa de Pós-Graduação em Engenharia Elétrica, Universidade Federal de Pernambuco, Recife 50670-901, PE, Brazil
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Author to whom correspondence should be addressed.
J. Low Power Electron. Appl. 2018, 8(4), 46; https://doi.org/10.3390/jlpea8040046
Received: 9 October 2018 / Revised: 12 November 2018 / Accepted: 16 November 2018 / Published: 22 November 2018
This paper introduced a matrix parametrization method based on the Loeffler discrete cosine transform (DCT) algorithm. As a result, a new class of 8-point DCT approximations was proposed, capable of unifying the mathematical formalism of several 8-point DCT approximations archived in the literature. Pareto-efficient DCT approximations are obtained through multicriteria optimization, where computational complexity, proximity, and coding performance are considered. Efficient approximations and their scaled 16- and 32-point versions are embedded into image and video encoders, including a JPEG-like codec and H.264/AVC and H.265/HEVC standards. Results are compared to the unmodified standard codecs. Efficient approximations are mapped and implemented on a Xilinx VLX240T FPGA and evaluated for area, speed, and power consumption. View Full-Text
Keywords: discrete cosine transform; approximation; multicriteria optimization; image/video compression discrete cosine transform; approximation; multicriteria optimization; image/video compression
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Coelho, D.F.G.; Cintra, R.J.; Bayer, F.M.; Kulasekera, S.; Madanayake, A.; Martinez, P.; Silveira, T.L.T.; Oliveira, R.S.; Dimitrov, V.S. Low-Complexity Loeffler DCT Approximations for Image and Video Coding. J. Low Power Electron. Appl. 2018, 8, 46.

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