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Research Article | Open Access |

High Precision DCT CORDIC Architectures for Maximum PSNR

Author 1: Imen Ben Saad Author 2: Sonia Mami Author 3: Yassine Hachaichi Author 4: Younes Lahbib Author 5: Abdelkader Mami
International Journal of Advanced Computer Science and Applications (IJACSA) · Vol. 8, No. 5 · Published 2017

DOI: https://doi.org/10.14569/IJACSA.2017.080561

Abstract

This paper proposes two optimal Cordic Loeffler based DCT (Discrete Cosine Transform algorithm) architectures: a fast and low Power DCT architecture and a high PSNR DCT architecture. The rotation parameters of CORDIC angles required for these architectures have been calculated using a MATLAB script. This script allows the variation of the angle’s precision from 10-1 to 10-4. The experimental results show that the fast and low Power DCT architecture correponds to the precision 10-1. Its complexity is even lower than the BinDCT which is a reference in terms of low complexity and its power has been enhanced in comparison with the conventional Cordic Loeffler DCT by 12 mW. The experimental results also show that the high PSNR DCT architecture corresponds to the precision 10-3 for which the PSNR has been improved by 6.55 dB in comparison with the conventional Cordic Loeffler DCT. Then, the hardware implementation and the generated RTL of some required Cordics are presented.

Keywords

How to Cite this Article

Saad, I. B., Mami, S., Hachaichi, Y., Lahbib, Y., & Mami, A. (2017). High Precision DCT CORDIC Architectures for Maximum PSNR. International Journal of Advanced Computer Science and Applications, 8(5). https://doi.org/10.14569/IJACSA.2017.080561

Saad, Imen Ben, et al.. "High Precision DCT CORDIC Architectures for Maximum PSNR." International Journal of Advanced Computer Science and Applications, vol. 8, no. 5, 2017, https://doi.org/10.14569/IJACSA.2017.080561.

@article{Saad2017,
  title     = {High Precision DCT CORDIC Architectures for Maximum PSNR},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {8},
  number    = {5},
  year      = {2017},
  publisher = {The Science and Information Organization},
  author    = {Imen Ben Saad and Sonia Mami and Yassine Hachaichi and Younes Lahbib and Abdelkader Mami},
  doi       = {10.14569/IJACSA.2017.080561},
  url       = {https://doi.org/10.14569/IJACSA.2017.080561}
}

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