TY - GEN
T1 - An optical and SAR image registration method based on bidirectional style transfer and hybrid feature descriptor
AU - Chu, Boce
AU - Chen, Jie
AU - Zeng, Hongcheng
AU - Chen, Jinyong
AU - Zhu, Jin
AU - Wang, Meirui
AU - Gao, Xiaoqian
N1 - Publisher Copyright:
© 2024 COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.
PY - 2024
Y1 - 2024
N2 - With the continuous development of modern science and technology, aerospace, aviation, and image sensor technologies are being constantly improved, and various new sensors and remote sensing platforms are emerging. Currently, the ability to obtain remote sensing data is improving continuously, and remote sensing data products are characterized by multiple spatial resolutions and multiple loads. Applications based on multi-source data fusion will replace single-source data applications in the future. The prerequisite for fusing data from different sources is that the spatial references for these data must be consistent. Therefore, it is imperative to conduct research on the methods for high-precision automatic registration of images from different sources in order to solve the problem of difficult registration of such images caused by different imaging mechanisms and effects. Taking the registration of optical and SAR images from different sources as an example, this paper presents a method of registering optical and SAR images based on bidirectional style transfer and hybrid feature descriptor. Firstly, a bidirectional style transfer network is used to convert the original optical and SAR images to pseudooptical and SAR images, thus achieving the homogenization of images from different sources. Subsequently, feature sets and hybrid feature descriptors are extracted from optical and SAR images, and the relationship between images from different sources in terms of feature matching is established to achieve high-precision automatic registration of optical and SAR images. The experimental results show that the method proposed in this paper is superior to traditional image registration methods in terms of both subjective perception and objective indicators such as RMSE and has achieved better registration results.
AB - With the continuous development of modern science and technology, aerospace, aviation, and image sensor technologies are being constantly improved, and various new sensors and remote sensing platforms are emerging. Currently, the ability to obtain remote sensing data is improving continuously, and remote sensing data products are characterized by multiple spatial resolutions and multiple loads. Applications based on multi-source data fusion will replace single-source data applications in the future. The prerequisite for fusing data from different sources is that the spatial references for these data must be consistent. Therefore, it is imperative to conduct research on the methods for high-precision automatic registration of images from different sources in order to solve the problem of difficult registration of such images caused by different imaging mechanisms and effects. Taking the registration of optical and SAR images from different sources as an example, this paper presents a method of registering optical and SAR images based on bidirectional style transfer and hybrid feature descriptor. Firstly, a bidirectional style transfer network is used to convert the original optical and SAR images to pseudooptical and SAR images, thus achieving the homogenization of images from different sources. Subsequently, feature sets and hybrid feature descriptors are extracted from optical and SAR images, and the relationship between images from different sources in terms of feature matching is established to achieve high-precision automatic registration of optical and SAR images. The experimental results show that the method proposed in this paper is superior to traditional image registration methods in terms of both subjective perception and objective indicators such as RMSE and has achieved better registration results.
KW - bidirectional style transfer
KW - feature point extraction
KW - hybrid feature descriptor
KW - image registration
KW - multi-source remote sensing data
UR - https://www.scopus.com/pages/publications/85184151029
U2 - 10.1117/12.3019591
DO - 10.1117/12.3019591
M3 - 会议稿件
AN - SCOPUS:85184151029
T3 - Proceedings of SPIE - The International Society for Optical Engineering
BT - Fourth International Conference on Geology, Mapping, and Remote Sensing, ICGMRS 2023
A2 - Wang, Yi
A2 - Chen, Tao
PB - SPIE
T2 - 4th International Conference on Geology, Mapping, and Remote Sensing, ICGMRS 2023
Y2 - 14 April 2023 through 16 April 2023
ER -