Efficient Approximate Computing Unit Architecture for Satellite Images

Abstract

Abstract Approximate computing plays a significant role in signal processing and image processing applications. Radix-8 approximate novel booth multiplier (R8ANBM) based on approximate novel booth encoder (ANBE) is proposed in this paper to validate approximate computing. The proposed design is synthesized and simulated in Xilinx ISE 13.2. The experimental results show that the proposed multiplier performs better in terms area, speed and energy consumption. The proposed R8ANBE reduced the number of 4 input LUTs by 23.07%, 17.94%, 19.87%, 16.66%, 13.46%, 8.33%, 12.82%, 9.61%, 12.17% and number of occupied slices by 22.33%, 30.09%, 25.24%, 29.12%, 14.56%, 17.47%, 13.59%, 12.62%, 17.47% when compared with the existing techniques such as conventional booth multiplier, R4ABM1, RAD64, ABM1, HLR-BM1, HLR-BM2, R8ABM1, R8ABM2, R8ABM3 respectively. It achieved the accuracy as 67.3% which is higher than exisitng approximate booth multipliers. The proposed R8ANBM is applied to image sharpening applications and the performances are analyzed in terms of error metrics such as ralative mean error distance, normalized mean error distance and peak signal to noise ratio. The above proposed system was implemented using 45nanometer technology library. With applications in low-power CMOS design, quantum computing, optical information processing, DNA computing, bioinformatics, and nanotechnology, there is an increasing interest in power minimization.