Energy Efficient 8 Point DCT Approximations: Theory and Hardware Architectures
Due to its remarkable energy compaction properties, the discrete cosine transform (DCT) is employed in a multitude of compression standards, such as JPEG and H.265/HEVC. Several low complexity integer approximations for the DCT have been proposed for both 1D and 2D signal analyses. The increasing demand for low complexity, energy efficient methods requires algorithms with even lower computational costs. In this paper, new 8 point DCT approximations with very low arithmetic complexity are presented. The new transforms are proposed based on pruning state of the art DCT approximations. The proposed algorithms were assessed in terms of arithmetic complexity, energy retention capability, and image compression performance. In addition, a metric combining performance and computational complexity measures was proposed. Results showed good performance and extremely low computational complexity. Introduced algorithms were mapped into systolic array digital architectures and physically realized as digital prototype circuits using FPGA technology and mapped to 45 nm CMOS technology. All hardware related metrics showed low resource consumption of the proposed pruned approximate transforms. The best proposed transform according to the introduced metric presents a reduction in power consumption of 21 25
Circuits Syst. Signal Process.