论文标题
学习通过可区分的波光学模拟器来建模和校准光学器件
Learning to Model and Calibrate Optics via a Differentiable Wave Optics Simulator
论文作者
论文摘要
我们提出了一种基于学习的新方法，以构建真实荧光显微镜的可区分计算模型。我们的模型可用于通过指定所需的输入输出数据直接从数据示例校准真实的光学设置，并通过指定所需的输入输出数据来校准。这种方法有望大大改善显微镜的设计，因为光学设置的当前模型的参数不能轻易适合真实数据。受深度学习最新进展的启发，我们的解决方案是构建可训练的波动模拟器作为可训练模块的组成，每个计算光波（WF）传播由于特定的光学元素而引起的。我们称我们的可区分模块波形，并在镜头，空气中的波传播，相机传感器和衍射元件（例如相罩）中显示重建结果。
We present a novel learning-based method to build a differentiable computational model of a real fluorescence microscope. Our model can be used to calibrate a real optical setup directly from data samples and to engineer point spread functions by specifying the desired input-output data. This approach is poised to drastically improve the design of microscopes, because the parameters of current models of optical setups cannot be easily fit to real data. Inspired by the recent progress in deep learning, our solution is to build a differentiable wave optics simulator as a composition of trainable modules, each computing light wave-front (WF) propagation due to a specific optical element. We call our differentiable modules WaveBlocks and show reconstruction results in the case of lenses, wave propagation in air, camera sensors and diffractive elements (e.g., phase-masks).
