Machine Learning for Time-Resolved Emission: Image Resolution Enhancement

S. Chef, C. T. Chua, Chee Lip Gan
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Abstract

This article describes a novel method for improving image resolution achieved using time-resolved photon emission techniques. Instead of directly generating images from photon counting, all detected photons are displayed as a point cloud in 3D space and a new higher-resolution image is generated based on probability density functions associated with photon distributions. Unsupervised learning algorithms identify photon distribution patterns as well as fainter emission sources.
时间分辨发射的机器学习:图像分辨率增强
本文描述了一种利用时间分辨光子发射技术提高图像分辨率的新方法。不是直接从光子计数生成图像,而是将所有检测到的光子显示为3D空间中的点云,并根据与光子分布相关的概率密度函数生成新的更高分辨率的图像。无监督学习算法识别光子分布模式以及微弱的发射源。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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