In structured illumination microscopy (SIM) for three-dimensional (3D) measurement, the vertical scanning position with the maximum modulation is implemented to reshape the surface topography. Generally, to obtain the modulation distribution for each scanning position, the modulation decoding algorithms mainly include temporal phase-shifting (TP) method and frequency analysis technique. In TP method, at least three images with a fixed phase-shift are required, which results in low efficiency and complex phase-shifting mechanism. Frequency analysis technique can realize modulation distribution from single image, but the high frequency information of the sample will be inevitably lost. In this paper, we propose a spatial area phase-shifting reconstruction method which requires only one exposure to decode the modulation distribution. In this technique, n pixels from one period of illuminated pattern are used to replace the corresponding n images in the temporal phase shift. Through combining the phase information of each pixel with the least square algorithm, the modulation distribution is achieved. The proposed method can achieve an accurate 3D reconstruction. Also, the high frequency information of the sample can be effectively retained compared with frequency analysis method. The simulations and experiments are conducted to verify the feasibility of this method, demonstrating the potential to be applied in high precision, complex surface and real-time measurement.

在用于三维 (3D) 测量的结构化照明显微镜 (SIM) 中，实施具有最大调制的垂直扫描位置以重塑表面形貌。通常，为了获得每个扫描位置的调制分布，调制解码算法主要包括时间相移（TP）方法和频率分析技术。在TP方法中，至少需要三个具有固定相移的图像，这导致效率低且相移机制复杂。频率分析技术可以实现单幅图像的调制分布，但不可避免地会丢失样本的高频信息。在本文中，我们提出了一种空间区域相移重建方法，该方法只需要一次曝光即可解码调制分布。在该技术中，来自一个照明图案周期的 n 个像素用于替换时间相移中的相应 n 个图像。通过将每个像素的相位信息与最小二乘算法相结合，实现调制分布。所提出的方法可以实现准确的3D重建。此外，与频率分析方法相比，可以有效保留样本的高频信息。通过仿真和实验验证了该方法的可行性，展示了其在高精度、复杂表面和实时测量中的应用潜力。实现调制分布。所提出的方法可以实现准确的3D重建。此外，与频率分析方法相比，可以有效保留样本的高频信息。通过仿真和实验验证了该方法的可行性，证明了其在高精度、复杂表面和实时测量中的应用潜力。实现调制分布。所提出的方法可以实现准确的3D重建。此外，与频率分析方法相比，可以有效保留样本的高频信息。通过仿真和实验验证了该方法的可行性，展示了其在高精度、复杂表面和实时测量中的应用潜力。