  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 1-D and 2-D signal analysis. The increasing demand
for low-complexity, energy efficient methods require 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 45nm 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%.
