Radial Distortion

Radial distortion, the warping of straight lines in images due to lens imperfections, is a significant challenge in computer vision and image processing. Current research focuses on developing robust methods for correcting this distortion, particularly in wide-angle and fisheye lenses, employing techniques like transformer-based architectures (e.g., Swin Transformers) and deep convolutional neural networks to achieve accurate and efficient compensation. These advancements are crucial for improving the accuracy of various applications, including 3D scene reconstruction, semantic segmentation, and autonomous driving, where accurate image geometry is paramount.