Imaging simulation and restoration for a mobile-based long-focus camera with optical stabilization

Abstract

Image stabilization technology of the mobile-based long-focus camera is an influential factor that limits the imaging quality. Among them, the periscope lens system is a common choice and is capable of compensating for the external vibration by rotating its prism. To further investigate the impact of residual vibration during the optical image stabilization process, we propose an imaging simulation method to quantify the degradation and construct the corresponding dataset for training. We decompose the degradation into translation perpendicular to the optical axis on the image plane and defocus parallel to the optical axis. The defocus blur pattern is modified to better reproduce the spatially variant deterioration caused by defocus. Constructing synthetic datasets through our proposed imaging simulation method significantly reduces the cost of training the post-processing network while enhancing the imaging quality. Extensive experiments demonstrate the accuracy of our proposed method and the superiority of our synthetic dataset.