Intensity saturation zone in the fringe pattern will appear when fringe projection profilometry is used to measure objects with high dynamic range reflectivity, which will affect the phase reconstruction of the tested object. In this paper, we proposed a fringe pattern inpainting method based on convolutional neural network (CNN) denoising regularization. Two fringe patterns under normal and short exposure time are respectively captured to quickly build a fringe with good quality using following steps. Otsu threshold method is used to determine highlight region by treating the modulation information of short exposure fringe pattern. Set an initial value for iteration by fusing the normal exposure fringe pattern with gray-adjusted short exposure fringe pattern. Realize fast fringe pattern inpainting using CNN denoising regularization and finally obtain a fringe to realize the high dynamic range phase reconstruction. Compared with other methods, the proposed method has advantage in effect and time of fringe inpainting.