DocumentCode :
270240
Title :
Improved 8-Point Approximate DCT for Image and Video Compression Requiring Only 14 Additions
Author :
Sadhvi Potluri, Uma ; Madanayake, A. ; Cintra, Renato J. ; Bayer, Fábio M. ; Kulasekera, Sunera ; Edirisuriya, A.
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Akron, Akron, OH, USA
Volume :
61
Issue :
6
fYear :
2014
fDate :
Jun-14
Firstpage :
1727
Lastpage :
1740
Abstract :
Video processing systems such as HEVC requiring low energy consumption needed for the multimedia market has lead to extensive development in fast algorithms for the efficient approximation of 2-D DCT transforms. The DCT is employed in a multitude of compression standards due to its remarkable energy compaction properties. Multiplier-free approximate DCT transforms have been proposed that offer superior compression performance at very low circuit complexity. Such approximations can be realized in digital VLSI hardware using additions and subtractions only, leading to significant reductions in chip area and power consumption compared to conventional DCTs and integer transforms. In this paper, we introduce a novel 8-point DCT approximation that requires only 14 addition operations and no multiplications. The proposed transform possesses low computational complexity and is compared to state-of-the-art DCT approximations in terms of both algorithm complexity and peak signal-to-noise ratio. The proposed DCT approximation is a candidate for reconfigurable video standards such as HEVC. The proposed transform and several other DCT approximations are mapped to systolic-array digital architectures and physically realized as digital prototype circuits using FPGA technology and mapped to 45 nm CMOS technology.
Keywords :
approximation theory; computational complexity; discrete cosine transforms; video coding; 2D DCT transforms; computational complexity; digital VLSI hardware; image compression; integer transforms; low circuit complexity; novel 8-point DCT approximation; peak signal-to-noise; video compression; video processing systems; Approximation algorithms; Approximation methods; Complexity theory; Discrete cosine transforms; Image coding; Sparse matrices; Approximate DCT; HEVC; image compression; low power consumption; low-complexity algorithms;
fLanguage :
English
Journal_Title :
Circuits and Systems I: Regular Papers, IEEE Transactions on
Publisher :
ieee
ISSN :
1549-8328
Type :
jour
DOI :
10.1109/TCSI.2013.2295022
Filename :
6803983
Link To Document :
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