Abstract
Inaccurate computing is found to be a high-speed, low-power and energy-efficient alternative to accurate computing for error-tolerant applications. In this context, this paper analyzes the usefulness of inaccurate computing for a digital image processing application, viz. digital image blending, which has been less explored. We analyze the use of inaccurate addition for image blending used in applications such as photo editing and computer graphics. For experimentation, we considered blending two digital images using accurate and inaccurate addition separately. We considered many inaccurate addition architectures which are suitable for implementation in both FPGA and ASIC design environments to perform a comparative analysis. We found that an inaccurate addition with an optimum inaccuracy produces a similar quality of blended image as obtained using accurate addition. The quality of blended images is quantified using standard metrics such as the peak signal-to-noise ratio and the structural similarity index measure. In particular, an inaccurate adder, M-HERLOA, was found to be preferable for image blending from the combined perspectives of quality of blended image, error metrics and design metrics. We implemented the accurate and inaccurate adders corresponding to an optimum inaccuracy in FPGA and ASIC design environments. We considered a Xilinx Artix-7 FPGA for an FPGA-based implementation and a 32/28 nm CMOS standard digital cell library for an ASIC type standard cell-based implementation. The results show that, for an FPGA-based implementation, M-HERLOA enables a reduction in delay by 13%, requires 50% fewer LUTs and 49% fewer registers and consumes 24.3% less on-chip power compared to the accurate high-speed FPGA adder while yielding a blended image of good quality. For an ASIC type standard cell-based implementation, M-HERLOA enables a reduction in delay by 64.6% (24.4%), requires 43% (82.4%), less area and dissipates 63% (67.8%) less power than the accurate carry ripple adder (carry look-ahead adder).
Subject
Electrical and Electronic Engineering,Computer Networks and Communications,Hardware and Architecture,Signal Processing,Control and Systems Engineering
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