Next Article in Journal
Enabling Energy-Efficient Physical Computing through Analog Abstraction and IP Reuse
Previous Article in Journal
Including Liquid Metal into Porous Elastomeric Films for Flexible and Enzyme-Free Glucose Fuel Cells: A Preliminary Evaluation
Article Menu

Export Article

Open AccessArticle
J. Low Power Electron. Appl. 2018, 8(4), 46; https://doi.org/10.3390/jlpea8040046

Low-Complexity Loeffler DCT Approximations for Image and Video Coding

1
Independent Researcher, Calgary AB, T3A 2H6, Canada
2
Department of Electrical and Computer Engineering, University of Calgary, 2500 University Dr. NW Calgary, AB T2N 1N4, Canada
3
Signal Processing Group, Departamento de Estatística, Universidade Federal de Pernambuco, Recife 50670-901, PE, Brazil
4
Departamento de Estatística and LACESM, Universidade Federal de Santa Maria, Santa Maria 97105-900, RS, Brazil
5
Department of Electrical and Computer Engineering, University of Akron, Akron, OH 44325, USA
6
Department of Electrical and Computer Engineering, Florida International University, Miami, FL 33174, USA
7
Friedrich-Alexander-Universität Erlangen-Nürnberg, 91054 Erlangen, Germany
8
Programa de Pós-Graduação em Computação, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre 91501-970, RS, Brazil
9
Programa de Pós-Graduação em Engenharia Elétrica, Universidade Federal de Pernambuco, Recife 50670-901, PE, Brazil
*
Author to whom correspondence should be addressed.
Received: 9 October 2018 / Revised: 12 November 2018 / Accepted: 16 November 2018 / Published: 22 November 2018
Full-Text   |   PDF [2327 KB, uploaded 29 November 2018]   |  

Abstract

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
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
SciFeed

Share & Cite This Article

MDPI and ACS Style

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.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
J. Low Power Electron. Appl. EISSN 2079-9268 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top