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.

翻译：鱼眼相机凭借其独特的宽视场角等特性，已在多个领域得到广泛应用。然而，与针孔相机相比，鱼眼相机存在显著畸变，导致拍摄物体图像失真。鱼眼相机畸变是数字图像处理中的常见问题，需要有效的校正技术来提升图像质量。本综述全面概述了用于鱼眼相机畸变校正的多种方法，探讨了利用多项式函数建模并校正径向畸变的多项式畸变模型，同时讨论了全景映射、网格映射、直接方法以及基于深度学习的替代方法。本综述重点阐述了每种方法的优势、局限性及最新进展，使读者能够根据具体需求做出明智选择。