Image Restoration via UAVFormer for Under-Display Camera of UAV

The exposed cameras of UAVs can shake, shift, or even malfunction under the influence of harsh weather, while the add-on devices (Dupont lines) are very vulnerable to dam-age. Although we can place a low-cost transparent film overlay around the camera to protect it, this would also introduce image degradation issues (such as oversaturation, astigmatism, etc). To tackle the image degradation problem caused by overlaying transparent film, in this paper we propose a novel method to enhance the visual experience by adapting a deep network with UAV characteristics. Specifically, we propose a customized Transformer named UAVFormer to recover the image, which has a key module at each stage based on the Swin Transformer with local awareness (LAT). In the end, we use an evidential fusion algorithm to integrate the generated images at each stage to obtain a high-quality result. Furthermore, we create a high-resolution under-display camera dataset to support the training and testing of compared models. Our model can conduct high-quality recovery of images of 2K resolution on some embedded devices (Raspberry Pi 4b) in realtime. The URL for the code at https://github.com/zzr-idam/UAVFormer.