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A New Algorithm to Derive High Performance and Low Hardware Cost DCT for HEVC.

Authors :
Jiang, Yuheng
Chen, Jiajia
Source :
IEEE Transactions on Computer-Aided Design of Integrated Circuits & Systems. Dec2022, Vol. 41 Issue 12, p5367-5379. 13p.
Publication Year :
2022

Abstract

Owing to its good compression ability, discrete cosine transform (DCT) is widely used in signal processing, including high-efficiency video coding (HEVC). For efficient implementation, approximate DCTs and integer DCTs were proposed, but the challenge in the tradeoff between coding performance and implementation cost always exists. To solve this problem, this article proposes a new algorithm to derive Int-DCT with good coding performance and low hardware cost. To address the multiobjective optimization problem, we extract information from the initially shortlisted transform matrices to derive the weighting factors for the different matrices properties. Those properties having a higher impact to the performance are assigned with higher weights and vice versa. Subsequently, an efficient search algorithm is proposed to shortlist those candidates which can lead to better coding performance evaluated by the proposed measure. Last but not the least, a splitting method is proposed to search the efficient extended double-base number system (EDBNS) representation of the coefficients for hardware implementation and select the solution which encounters the lowest cost. The experimental results in ASIC demonstrate that the implementation area and power cost of designs by the new algorithm are reduced by at least 11.1% and 17.5% for 32-point transform, respectively, over other competing algorithms. Meanwhile, the transforms generated by the proposed algorithm causes negligible impact to coding performance compared to the original transforms in HEVC. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
02780070
Volume :
41
Issue :
12
Database :
Academic Search Index
Journal :
IEEE Transactions on Computer-Aided Design of Integrated Circuits & Systems
Publication Type :
Academic Journal
Accession number :
160651819
Full Text :
https://doi.org/10.1109/TCAD.2022.3166670