Power–Area-Optimized Approximate Multiplier Design for Image Fusion

• Published in: Circuits, systems, and signal processing Vol. 43; no. 4; pp. 2288 - 2319
• Main Authors: Thakur, Garima, Sohal, Harsh, Jain, Shruti
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.04.2024; Springer Nature B.V
• Subjects: Accuracy; Algorithms; Approximation; Circuits; Circuits and Systems; Compressors; Computer engineering; Computer vision; Design; Design optimization; Efficiency; Electrical Engineering; Electronics and Microelectronics; Energy; Engineering; Instrumentation; Iterative methods; Multimedia; Multiplication & division; Multipliers; Neural networks; Optimization; Signal processing; Signal,Image and Speech Processing; Image blending; Compressors; Han–Carlson adder; Error-tolerant application; Approximate multiplier
• ISSN: 0278-081X; 1531-5878
• DOI: 10.1007/s00034-023-02559-0

In this paper, three approximate multiplier architectures are proposed: area-optimized approximate multiplier (AOM), power-optimized approximate multiplier (POM), and power- and area-optimized approximate multiplier (PAOM). These designs are implemented using speculative Han–Carlson adder and compressor-based multiplier blocks. Han–Carlson adder is used as the basic adder block in the final addition stage of all the three approximate multiplier designs. Different types of compressors (3:2, 4:2, 5:2, 6:2, 7:2, 8:2) are used for the implementation of the energy-efficient approximate multiplier blocks. All the simulations are performed on VIVADO design tool. Also, the designed multipliers are validated for image blending (an error-tolerant) application. The proposed power optimization approximate multiplier shows 0.86%, 10.54% PSNR improvement in comparison with area optimization approximate multiplier and power and area optimization approximate multiplier, respectively.