Traditional wavefront-detection-based deconvolution methods depend on time synchronization, where far-field images are captured simultaneously with wavefront measurements using a Shack-Hartmann wavefront sensor. This synchronization facilitates far-field image restoration via deconvolution. However, in practical applications, most adaptive optics systems lack time synchronization, which makes accurate motion blur kernel estimation challenging. To address this problem, we propose a multiscale optimal blur kernel estimation method. The proposed method effectively estimates motion blur kernels without requiring time synchronization. This method was applied to wavefront-detection-based deconvolution techniques and conducted simulations using two sets of extended targets. The results demonstrate that the proposed method effectively estimates motion blur kernels, offering a novel solution for image restoration in non-time-synchronized adaptive optics systems.