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Energy-Efficient 8-Point DCT Approximations: Theory and Hardware Architectures

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Abstract

Due to its remarkable energy compaction properties, the discrete cosine transform (DCT) is employed in a multitude of compression standards, such as JPEG and H.265/HEVC. Several low-complexity integer approximations for the DCT have been proposed for both 1D and 2D signal analyses. The increasing demand for low-complexity, energy-efficient methods requires algorithms with even lower computational costs. In this paper, new 8-point DCT approximations with very low arithmetic complexity are presented. The new transforms are proposed based on pruning state-of-the-art DCT approximations. The proposed algorithms were assessed in terms of arithmetic complexity, energy retention capability, and image compression performance. In addition, a metric combining performance and computational complexity measures was proposed. Results showed good performance and extremely low computational complexity. Introduced algorithms were mapped into systolic-array digital architectures and physically realized as digital prototype circuits using FPGA technology and mapped to 45 nm CMOS technology. All hardware-related metrics showed low resource consumption of the proposed pruned approximate transforms. The best proposed transform according to the introduced metric presents a reduction in power consumption of 21–25 %.

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Acknowledgments

This work was partially supported by CNPq, FACEPE, and FAPERGS (Brazil), and by the College of Engineering at the University of Akron, Akron, OH, USA.

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Authors and Affiliations

  1. Signal Processing Group, Departamento de Estatística, Universidade Federal de Pernambuco, Recife, PE, Brazil

    Renato J. Cintra & André Leite

  2. Equipe Cairn, IRISA-INRIA, Université de Rennes 1, Rennes, France

    Renato J. Cintra

  3. LIRIS, Institut National des Sciences Appliquées, Lyon, France

    Renato J. Cintra

  4. Departamento de Estatística and LACESM, Universidade Federal de Santa Maria, Santa Maria, RS, Brazil

    Fábio M. Bayer

  5. Graduate Program in Electrical Engineering and the Signal Processing Group, Departamento de Estatística, Universidade Federal de Pernambuco, Recife, PE, Brazil

    Vítor A. Coutinho

  6. Department of Electrical and Computer Engineering, The University of Akron, Akron, OH, USA

    Sunera Kulasekera & Arjuna Madanayake

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  1. Renato J. Cintra
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  2. Fábio M. Bayer
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Correspondence to Fábio M. Bayer.

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Cintra, R.J., Bayer, F.M., Coutinho, V.A. et al. Energy-Efficient 8-Point DCT Approximations: Theory and Hardware Architectures. Circuits Syst Signal Process 35, 4009–4029 (2016). https://doi.org/10.1007/s00034-015-0233-z

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