The complex reflective properties of highly reflective surfaces bring overexposure and underexposure problems to surface structured light technology. In order to reconstruct the measured surface completely and accurately, a multiple exposure method is proposed in this paper. The proposed method can predict the exposure time according to the reflective intensity of the measured surface. Firstly, the camera response curve of the imaging system is obtained by projecting a series of uniform gray images at different exposure times, and the irradiance image that can reflect the reflection intensity of the measured surface is calculated. Then, the fuzzy C-means clustering method is used to adaptively segment different irradiance regions of the target and obtain the central irradiance of each region. The optimal exposure time is predicted for different reflection regions based on the camera response curve. Finally, the 3D reconstruction of the highly reflective surface is realized by combining the multiple exposure fusion algorithm. The experimental results show that the proposed method can simultaneously reconstruct the strongly reflective area and the excessively dark area of the aluminum alloy surface, with a reconstruction error of less than 0.5 mm, the maximum deviation reduced by 74.78%, and the standard deviation reduced by 48.96%. The proposed method can correctly predict the exposure time according to regional reflection characteristics, effectively overcome the problems of phase loss and phase distortion caused by regional overexposure and regional darkness, and completely and accurately reconstruct different reflection regions of highly reflective surfaces.