Structured illumination microscopy (SIM) reconstructs a super-resolved image from multiple raw images; hence, acquisition speed is limited, making it unsuitable for dynamic scenes. We propose a new method, Speckle Flow SIM, that models sample motion during the data capture in order to reconstruct dynamic scenes with super-resolution. Speckle Flow SIM uses fixed speckle illumination and relies on sample motion to capture a sequence of raw images. Then, the spatio-temporal relationship of the dynamic scene is modeled using a neural space-time model with coordinate-based multi-layer perceptrons (MLPs), and the motion dynamics and the super-resolved scene are jointly recovered. We validated Speckle Flow SIM in simulation and built a simple, inexpensive experimental setup with off-the-shelf components. We demonstrated that Speckle Flow SIM can reconstruct a dynamic scene with deformable motion and 1.88x the diffraction-limited resolution in experiment.

翻译：结构化光化显微镜( SIM) 从多个原始图像中重建一个超级解析图像; 因此, 获取速度有限, 使其不适合动态场景 。 我们提出一种新的方法, 即 Speckle Flow SIM, 在数据采集过程中模型样本运动, 以便用超分辨率重建动态场景 。 Speckle Flow SIM 使用固定的分光光光化光化, 并依靠样本运动来捕捉原始图像序列 。 然后, 动态场景的波形- 时空关系建模时, 使用基于协调的多层透视器( MLPs) 的神经空间时间模型来建模, 并联合恢复运动动态和超级解析场景。 我们在模拟中验证了 Speckle Flow SIM, 并建立了一个简单、 廉价的实验设备, 使用现成部件组成。 我们证明 Speclekle Flow SIM 可以用变形动作和1.88x diflam 分辨率来重建动态场景 。