频率梳与深度学习结合实现快速高保真鬼成像
Fast, High-Fidelity Ghost Imaging Merges Frequency Combs and Deep Learning
鬼成像用结构照明与单像素探测器之间的关联测量取代像素化传感器。研究人员把光学频率梳与深度学习结合,实现更快、保真度更高的鬼成像。
原文展示了频率梳照明与AI重建的结合,是计算成像中光学与AI协同的典型案例
中文译文尚未生成,当前展示的是已获取的原文文本。
Ghost imaging, a technique that reframes image formation by replacing pixelated sensors with correlation measurements between structured illumination and a single-pixel detector, offers distinct advantages in low-light settings, through scattering media, and on platforms where hardware size is limited. But while, in theory, ghost imaging provides a satisfactory solution to capturing images in photon-starved or size-constrained environments, in practice, it has been of limited use. Conventional ghost imaging is fundamentally slow, because it typically uses spatial light modulators or swept-frequency lasers to generate uncorrelated, 2D illumination patterns and project them onto the target sequentially. The use of slow,...
来源:Photonics.com · photonics.com