Bingqi Cai, Yang Huang, Lingzhi Tang, Tianyu Wang, Chen Wang, Qingqing Sun, David Wei Zhang, Lin Chen
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引用次数: 1
摘要
图像稳定是机器视觉中的一个重要领域,旨在消除由于相机或物体抖动引起的图像模糊或失真。然而,传统的稳像技术往往存在需要复杂设备或大量计算资源的缺点,导致效率低下。相比之下,人的视网膜执行一个高效的一体化系统,包括光刺激的检测和处理。本研究提出了一种基于CsxFAyMA1-x-yPb(IzBr1-z)3的全光控视omorphic忆阻器,集感知、存储和处理功能于一体。这种忆阻器在图像稳定方面具有显著的优势。它能够使用红光(630 nm)的特定强度(分别为11.8和0.9 mW cm - 2)正调制和负调制其电导。为了验证该方法的有效性,进行了手写体数字识别仿真。特定光刺激的应用有效地突出了模糊图像的特征。处理后的图像随后被输入电导映射神经网络以进行快速识别。值得注意的是,经过19000次迭代后,处理后的图像识别率达到83.5%,超过了模糊图像(19000次迭代后仅为56.2%)。这些结果突出了视纯记忆电阻器作为下一代图像稳定系统硬件基础的巨大潜力。
All-Optically Controlled Retinomorphic Memristor for Image Processing and Stabilization
Image stabilization is a crucial field in machine vision, aiming to eliminate image blurring or distortion caused by the camera or object jitter. However, traditional image stabilization techniques often suffer from the drawbacks of requiring complex equipment or extensive computing resources, resulting in inefficiencies. In contrast, the human retina performs a highly efficient all-in-one system, encompassing the detection and processing of light stimuli. In this study, an all-optically controlled retinomorphic memristor based on the CsxFAyMA1-x-yPb(IzBr1-z)3 is proposed, which integrates perception, storage, and processing functions. This memristor exhibits significant advantages in image stabilization. It is capable of positively and negatively modulating its conductance using specific intensities (11.8 and 0.9 mW cm−2, respectively) of red light (630 nm). To demonstrate the effectiveness of the proposed approach, handwritten digit recognition simulations are conducted. The application of specific light stimuli effectively highlights the characteristics of blurred images. The processed images are then fed into a conductance-mapped neural network for rapid recognition. Remarkably, the recognition rates of the processed images reach 83.5% after 19 000 iterations, surpassing the performance of blurred images (only 56.2% after 19 000 iterations). These results highlight the immense potential of retinomorphic memristors as the hardware foundation for next-generation image stabilization systems.
期刊介绍:
Firmly established as a top-tier materials science journal, Advanced Functional Materials reports breakthrough research in all aspects of materials science, including nanotechnology, chemistry, physics, and biology every week.
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