AI RESEARCH
Enhanced Self-Supervised Multi-Image Super-Resolution for Camera Array Images
arXiv CS.CV
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ArXi:2604.06816v1 Announce Type: cross Conventional multi-image super-resolution (MISR) methods, such as burst and video SR, rely on sequential frames from a single camera. Consequently, they suffer from complex image degradation and severe occlusion, increasing the difficulty of accurate image restoration. In contrast, multi-aperture camera-array imaging captures spatially distributed views with sampling offsets forming a stable disk-like distribution, which enhances the non-redundancy of observed data. Existing MISR algorithms fail to fully exploit these unique properties.