Memristor augmented approximate adders and subtractors for image processing applications: An approach

Abstract Approximate computing aims at reducing circuit complexity and delay, by allowing leverages in the output for a certain combination of inputs. The reduction in circuit complexity is achieved by minimizing the number of components in the circuit. This paper proposes a plausible approach towards approximate computing with memristors for designing memristor based approximate full adder and subtractor with logic minimization technique. The validation of our proposed approximate adder is verified by designing an 8-bit Ripple Carry Adder (RCA) to perform bitwise pixel addition of two gray scale images of the same size and compare the design with images obtained by exact addition method. Similarly, we have affirmed that the designed 8-bit Ripple Borrow Subtractor (RBS) is verified on foreground detection. Furthermore, to corroborate the above observation, performance metrics like Mean Square Error (MSE), Peak Signal to Noise Ratio (PSNR), Structural Content (SC), Mean Absolute Error (MAE), Average Distance (AD), Mean Average Distance (MAD) and Normalized Absolute Error (NAE) are deduced in MATLAB®. Owing to the logic minimization technique, for a certain combination of inputs, the MSE has been found to be predominant and its impact on PSNR is studied.