Many papers have reviewed remote sensing image segmentation (RSIS) algorithms currently. Those existing surveys are insufficiently exhaustive to sort out the various RSIS methods, it is impossible to comprehensively compare characteristics of different RSIS methods. In addition, the segmentation efficiency and accuracy of the RSIS methods cannot always meet the subsequent image analysis requirements. Thus, a clear comparative analysis of various RSIS methods is essential to provide an in-depth understanding of RSIS and theoretical ideas for conducting in-depth research in the future. The goal of this article is to provide readers with the latest information on optical RSIS technology. Comparative measures of these methods are provided in terms of conceptual details, the merits and demerits, and the performance of various RSIS methods. Moreover, various RSIS methods’ experiments are carried out on optical images using the NWPU VHR-10 public remote sensing datasets. Through the review of optical RSIS methods, this paper provides data as complete as possible for further related research and development of RSIS methods.

当前，许多论文已经综述了遥感图像分割（RSIS）算法。这些现有的调查还不足以详尽地整理出各种RSIS方法，因此无法全面比较不同RSIS方法的特征。另外，RSIS方法的分割效率和准确性不能总是满足随后的图像分析要求。因此，对RSIS的各种方法进行清晰的比较分析对于深入了解RSIS和将来进行深入研究的理论思想至关重要。本文的目的是为读者提供有关光学RSIS技术的最新信息。根据概念细节，优缺点和各种RSIS方法的性能，提供了这些方法的比较措施。此外，使用NWPU VHR-10公共遥感数据集在光学图像上进行了各种RSIS方法的实验。通过回顾光学RSIS方法，本文为RSIS方法的进一步相关研究和开发提供了尽可能完整的数据。