The fisheye camera, with its unique wide field of view and other
characteristics, has found extensive applications in various fields. However,
the fisheye camera suffers from significant distortion compared to pinhole
cameras, resulting in distorted images of captured objects. Fish-eye camera
distortion is a common issue in digital image processing, requiring effective
correction techniques to enhance image quality. This review provides a
comprehensive overview of various methods used for fish-eye camera distortion
correction. The article explores the polynomial distortion model, which
utilizes polynomial functions to model and correct radial distortions.
Additionally, alternative approaches such as panorama mapping, grid mapping,
direct methods, and deep learning-based methods are discussed. The review
highlights the advantages, limitations, and recent advancements of each method,
enabling readers to make informed decisions based on their specific needs.

鱼眼相机的畸变修正方法进行了综述，包括多项式畸变模型、全景映射、网格映射、直接方法和基于深度学习的方法。文章强调了每种方法的优点、限制和最新进展，以帮助读者根据自己的具体需求做出明智的决策。