Abstract
In this paper we present a low complexity discrete cosine transform (DCT) architecture based on computation re-use in vector-scalar product. 1-D DCT operation is expressed as additions of vector-scalar products and basic common computations are identified and shared to reduce computational complexity in 1-D DCT operation. Compared to general distributed arithmetic based DCT architecture, the proposed DCT shows 38% of area and 18% of power savings with little performance degradation. We also propose an efficient method to trade off image quality for computational complexity. The approach is based on the modification of DCT bases in bit-wise manner and different computational complexity/image quality trade-off levels are suggested. Finally, based on the above approaches, we propose a low complexity DCT architecture, which can dynamically reconfigure from one trade-off level to another. The reconfigurable DCT architecture can achieve power savings ranging from 28% to 56% for 3 different trade-off levels.
Original language | English |
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Pages (from-to) | 399-410 |
Number of pages | 12 |
Journal | Journal of Signal Processing Systems |
Volume | 53 |
Issue number | 3 |
DOIs | |
Publication status | Published - 2008 Dec |
Bibliographical note
Funding Information:This research was funded by Semiconductor Research Corporation.
Keywords
- Discrete cosine transform
- Low computational complexity
- Low power VLSI design
ASJC Scopus subject areas
- Control and Systems Engineering
- Theoretical Computer Science
- Signal Processing
- Information Systems
- Modelling and Simulation
- Hardware and Architecture