Fisheye lens gains increasing applications in computational photography and
assisted driving because of its wide field of view (FoV). However, the fisheye
image generally contains invalid black regions induced by its imaging model. In
this paper, we present a FisheyeEX method that extends the FoV of the fisheye
lens by outpainting the invalid regions, improving the integrity of captured
scenes. Compared with the rectangle and undistorted image, there are two
challenges for fisheye image outpainting: irregular painting regions and
distortion synthesis. Observing the radial symmetry of the fisheye image, we
first propose a polar outpainting strategy to extrapolate the coherent
semantics from the center to the outside region. Such an outpainting manner
considers the distribution pattern of radial distortion and the circle
boundary, boosting a more reasonable completion direction. For the distortion
synthesis, we propose a spiral distortion-aware perception module, in which the
learning path keeps consistent with the distortion prior of the fisheye image.
Subsequently, a scene revision module rearranges the generated pixels with the
estimated distortion to match the fisheye image, thus extending the FoV. In the
experiment, we evaluate the proposed FisheyeEX on three popular outdoor
datasets: Cityscapes, BDD100k, and KITTI, and one real-world fisheye image
dataset. The results demonstrate that our approach significantly outperforms
the state-of-the-art methods, gaining around 27% more content beyond the
original fisheye image.

本文提出了一种采用极坐标补齐以及螺旋失真感知模块的鱼眼图像外推方法 FisheyeEX，它能够有效处理鱼眼镜头成像模型中的无效黑色区域，并且在实验中表现出了很高的性能提升。