Fisheye Image Rectification

Fisheye image rectification aims to transform the highly distorted images from fisheye lenses into undistorted, perspective-correct views. Recent research focuses on developing robust methods that handle variations in optical center position and leverage the inherent distortion patterns within fisheye images, employing techniques like self-supervised learning, GANs, and Transformers to achieve accurate rectification. These advancements improve the quality and efficiency of rectification, particularly for video processing and real-world applications, leading to more reliable results in areas such as computer vision, robotics, and surveillance.