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

机译:偶极子耦合纳米磁体的图像处理:噪声抑制和边缘增强检测

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Hardware-based image processing offers speed and convenience not found in software-centric approaches. Here, we show theoretically that a 2-D 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.
机译:基于硬件的图像处理提供了以软件为中心的方法所没有的速度和便利性。在这里,我们从理论上表明,在压电基板上描绘的偶极耦合椭圆形纳米磁铁的二维周期阵列可以充当特定图像处理功能的动力学系统。每个纳米磁铁都有两个稳定的磁化状态,可对像素颜色(黑色或白色)进行编码。首先将包含黑白像素的图像转换为电压状态,然后将其映射为具有磁隧道结(MTJ)的纳米磁体阵列的磁化状态。以后使用相同的MTJ读取处理后的像素颜色。纳米磁铁之间的偶极相互作用实现了特定的图像处理任务,例如降噪和边缘增强检测。这些功能是通过在纳米压电体上施加全局应变而在压电基体上下降的电压来触发的。包含任意数量的黑白像素的图像可以在几纳秒内以非常低的能源成本进行处理。

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