Multi-image super-resolution (MISR) allows to increase the spatial resolution of a low-resolution (LR) acquisition by combining multiple images carrying complementary information in the form of sub-pixel offsets in the scene sampling, and can be significantly more effective than its single-image counterpart. Its main difficulty lies in accurately registering and fusing the multi-image information. Currently studied settings, such as burst photography, typically involve assumptions of small geometric disparity between the LR images and rely on optical flow for image registration. We study a MISR method that can increase the resolution of sets of images acquired with arbitrary, and potentially wildly different, camera positions and orientations, generalizing the currently studied MISR settings. Our proposed model, called EpiMISR, moves away from optical flow and explicitly uses the epipolar geometry of the acquisition process, together with transformer-based processing of radiance feature fields to substantially improve over state-of-the-art MISR methods in presence of large disparities in the LR images.

翻译：多图像超分辨率（MISR）通过结合多幅携带场景采样亚像素偏移互补信息的图像，能够提高低分辨率（LR）采集的空间分辨率，其效果通常显著优于单图像超分辨率。其主要难点在于精确配准与融合多图像信息。当前研究场景（如连拍摄影）通常假设LR图像间存在较小的几何差异，并依赖光流法进行图像配准。本文研究了一种MISR方法，可适用于任意且可能存在极大差异的相机位姿与方向所采集的图像集，从而泛化了现有MISR研究场景。我们提出的模型EpiMISR摒弃了光流法，而显式采用采集过程的极线几何约束，并结合基于Transformer的辐射特征场处理，在LR图像存在大视差时显著超越了现有最优MISR方法。