Image line segment detection is a fundamental problem in computer vision and remote sensing. Although numerous state-of-the-art methods have shown great performance for straight line segment detection, line segment detection for distorted images without undistortion is still a challenging problem. Besides, there is a lack of a unified line segment detection framework for both distorted and undistorted images. To address these two problems, we propose a novel learning-based Unified Line Segment Detection method (i.e., ULSD) for distorted and undistorted images in this paper. Specifically, we first propose a novel equipartition point-based Bezier curve representation to model arbitrary distorted line segments. Then the line segment detection is tackled by equipartition point regression with an end-to-end trainable neural network. Consequently, the proposed ULSD is independent of camera distortion parameters and does not need any undistortion preprocessing. In the experiments, the proposed method is firstly evaluated on the pinhole, fisheye, and spherical image datasets, respectively, as well as trained and tested on the mixed dataset with differently distorted images. The experimental results on each distortion model show that the proposed ULSD is more competitive than the state-of-the-art methods for both accuracy and efficiency, especially for the results of the unified model trained on the mixed datasets, thus demonstrating the effectiveness and generality of the proposed ULSD to real-world scenarios. The source code and datasets are available at https://github.com/lh9171338/ULSD-ISPRS.

图像线段检测是计算机视觉和遥感中的一个基本问题。尽管许多最先进的方法在直线段检测方面表现出出色的性能，但在没有不失真的情况下对失真图像进行线段检测仍然是一个具有挑战性的问题。此外，对于失真和未失真图像都缺乏统一的线段检测框架。为了解决这两个问题，我们在本文中提出了一种新颖的基于学习的统一线段检测方法（即，ULSD）用于失真和未失真图像。具体来说，我们首先提出了一种新的基于均分点的贝塞尔曲线表示来模拟任意扭曲的线段。然后使用端到端可训练神经网络通过均分点回归处理线段检测。最后，所提出的 ULSD 与相机失真参数无关，不需要任何非失真预处理。在实验中，所提出的方法首先分别在针孔、鱼眼和球面图像数据集上进行评估，并在具有不同失真图像的混合数据集上进行训练和测试。每个失真模型的实验结果表明，所提出的 ULSD 在准确性和效率方面都比最先进的方法更具竞争力，尤其是在混合数据集上训练的统一模型的结果，从而证明了有效性和所提出的 ULSD 对现实世界场景的普遍性。源代码和数据集可从 https://github.com/lh9171338/ULSD-ISPRS 获得。