Image Processing with Dipole-Coupled Nanomagnets: Noise Suppression and Edge Enhancement Detection

TL;DR

This paper proposes a novel hardware approach using dipole-coupled nanomagnet arrays on piezoelectric substrates for fast, low-energy image processing tasks like noise suppression and edge detection.

Contribution

It introduces a theoretical framework for using nanomagnet arrays with magneto-tunneling junctions to perform image processing functions through strain-induced dipole interactions.

Findings

Nanomagnet arrays can perform noise reduction and edge detection.

Processing occurs in a few nanoseconds with low energy consumption.

The method encodes pixels via magnetization states and reads results with MTJs.

Abstract

Hardware based image processing offers speed and convenience not found in software-centric approaches. Here, we show theoretically that a two-dimensional periodic array of dipole-coupled elliptical nanomagnets, delineated on a piezoelectric substrate, can act as a dynamical system for specific image processing functions. Each nanomagnet has two stable magnetization states that encode pixel color (black or white). An image containing black and white pixels is first converted to voltage states and then mapped into the magnetization states of a nanomagnet array with magneto-tunneling junctions (MTJs). The same MTJs are employed to read out the processed pixel colors later. Dipole interaction between the nanomagnets implements specific image processing tasks such as noise reduction and edge enhancement detection. These functions are triggered by applying a global strain to the nanomagnets with a voltage dropped across the piezoelectric substrate. An image containing an arbitrary number of black and white pixels can be processed in few nanoseconds with very low energy cost.