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Proceedings Paper

Low-complexity multiplierless DCT approximations for low-power HEVC digital IP cores
Author(s): Sunera C. Kulasekera; Arjuna Madanayake; Renato J. Cintra; Fabio M. Bayer; Uma Potluri
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Paper Abstract

Image and video compression plays a major role in multimedia transmission. Specifically the discrete cosine transform (DCT) is the key tool employed in a vast variety of compression standards such as H.265/HEVC due to its remarkable energy compaction properties. Rapid growth in digital imaging applications, such as multimedia and automatic surveillance that operates with limited bandwidths has led to extensive development of video processing systems. The main objective of this paper is to discuss some DCT approximations equipped with fast algorithms which require minimum addition operations and zero multipliers or bit-shifting operations leading to significant reductions in chip area and power consumption compared to conventional DCT algorithms. We provide complete design details for several k × k, k = 8, 16 blocked 2-D algorithms for DCT computation with video evaluation using HEVC software encoder. Custom digital architectures are proposed, simulated and implemented on Xilinx FPGAs and verified in conjunction with software models.

Paper Details

Date Published: 19 June 2014
PDF: 7 pages
Proc. SPIE 9089, Geospatial InfoFusion and Video Analytics IV; and Motion Imagery for ISR and Situational Awareness II, 90890W (19 June 2014); doi: 10.1117/12.2050715
Show Author Affiliations
Sunera C. Kulasekera, The Univ. of Akron (United States)
Arjuna Madanayake, The Univ. of Akron (United States)
Renato J. Cintra, Univ. Federal de Pernambuco (Brazil)
Fabio M. Bayer, Univ. Federal de Santa Maria (Brazil)
Uma Potluri, The Univ. of Akron (United States)

Published in SPIE Proceedings Vol. 9089:
Geospatial InfoFusion and Video Analytics IV; and Motion Imagery for ISR and Situational Awareness II
Matthew F. Pellechia; Kannappan Palaniappan; Shiloh L. Dockstader; Paul B. Deignan; Peter J. Doucette; Donnie Self, Editor(s)

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