摘要
Abstract
It is quite difficult to extract features from heterogeneous aerospace images,and the image matching accu-racy is relatively low,which has a negative impact on the precise target positioning of unmanned aerial vehicles(UAVs).The SuperPoint-SuperGlue algorithm has been widely applied in the field of image matching in recent years due to its char-acteristics such as self-supervision,easy training,and high accuracy.However,in the field of heterogeneous aerospace im-age matching,the feature extraction ability of SuperPoint still needs to be improved.In order to improve the matching accu-racy of heterogeneous aerospace images,this paper proposes a heterogeneous aerospace image matching algorithm based on the improved SuperPoint.Firstly,the spatial group-wise enhance(SGE)module and the global attention mechanism(GAM)are introduced into the SuperPoint encoder to form a supplementary encoder,which to a certain extent solves the problems of uneven distribution of image features and the difficulty in extracting features from weakly textured images.Secondly,to further enhance the feature extraction ability of the algorithm,the supplementary encoder is connected in parallel with the original SuperPoint encoder to form a combined encoder.By combining the advantages of the two,it can extract image fea-tures with greater differences,reduce the false matching of feature points in similar regions,and improve the matching accu-racy of heterogeneous aerospace images.Finally,through experimental verification,within the error range of 80 pixels on the UAV-VisLoc dataset,the number of matchable images can reach 82.14%.Compared with the original SuperPoint algo-rithm,the number of matchable images within the error range of 80 pixels has increased by 6.05%.Compared with other ad-vanced algorithms,the number of matchable images within each pixel error range has increased.The experiments show that the algorithm proposed in this paper can effectively solve the problems such as weak feature extraction ability and uneven feature distribution in the matching of heterogeneous aerospace images.关键词
空天异源/图像匹配/无人机/SuperPoint/SuperGlue/编码器Key words
heterogeneous in aerospace domain/image matching/UAV/SuperPoint/SuperGlue/encoder分类
信息技术与安全科学
