With the rapid development of digital earth,smart city,and digital twin technology,the demands of three-dimensional model data’s application is getting higher and higher.These data tend to be multi-objectification,mu...With the rapid development of digital earth,smart city,and digital twin technology,the demands of three-dimensional model data’s application is getting higher and higher.These data tend to be multi-objectification,multi-type,multi-scale,complex spatial relationship,and large amount,which brings great challenges to the efficient organization of them.This paper mainly studies the organization of three-dimensional model data,and the main contributions are as follows:1)A integer coding method of three dimensional multi-scale grid is proposed,which can reduce the four-dimensional(spatial dimension and scale dimension)space into one-dimensional,and has better space and scale clustering characteristics by comparing with various types of grid coding.2)The binary algebra calculation method is proposed to realize the basic spatial relationship calculation of three-dimensional grid,which has higher spatial relationship computing ability than 3D-Geohash method;3)The multi-scale integer coding method is applied to the data organization of three-dimensional city model,and the experiment results show that:it is more efficient and stable than the threedimensional R-tree index and Geohash coding method in the establishment of index and the query of three dimensional space.展开更多
Remote sensing image registration is still a challenging task owing to the significant influence of nonlinear differences between remote sensing images.To solve this problem,this paper proposes a novel approach with r...Remote sensing image registration is still a challenging task owing to the significant influence of nonlinear differences between remote sensing images.To solve this problem,this paper proposes a novel approach with regard to feature-based remote sensing image registration.There are two key contributions:1)we bring forward an improved strategy of composite nonlinear diffusion filtering according to the scale factors in multi-scale space and 2)we design a gradually decreasing resolution of multi-scale pyramid space.And a binary code string is served as feature descriptors to improve matching efficiency.Extensive experiments of different categories of remote image datasets on feature extraction and feature registration are performed.The experimental results demonstrate the superiority of our proposed scheme compared with other classical algorithms in terms of correct matching ratio,accuracy and computation efficiency.展开更多
基金National Key R&D Program of China[Grant Number 2018YFB0505304]National Natural Science Foundation of China[Grant Number 41671409].
文摘With the rapid development of digital earth,smart city,and digital twin technology,the demands of three-dimensional model data’s application is getting higher and higher.These data tend to be multi-objectification,multi-type,multi-scale,complex spatial relationship,and large amount,which brings great challenges to the efficient organization of them.This paper mainly studies the organization of three-dimensional model data,and the main contributions are as follows:1)A integer coding method of three dimensional multi-scale grid is proposed,which can reduce the four-dimensional(spatial dimension and scale dimension)space into one-dimensional,and has better space and scale clustering characteristics by comparing with various types of grid coding.2)The binary algebra calculation method is proposed to realize the basic spatial relationship calculation of three-dimensional grid,which has higher spatial relationship computing ability than 3D-Geohash method;3)The multi-scale integer coding method is applied to the data organization of three-dimensional city model,and the experiment results show that:it is more efficient and stable than the threedimensional R-tree index and Geohash coding method in the establishment of index and the query of three dimensional space.
基金supported by National Nature Science Foundation of China(Nos.61640412 and 61762052)the Natural Science Foundation of Jiangxi Province(No.20192BAB207021)the Science and Technology Research Projects of Jiangxi Province Education Department(Nos.GJJ170633 and GJJ170632).
文摘Remote sensing image registration is still a challenging task owing to the significant influence of nonlinear differences between remote sensing images.To solve this problem,this paper proposes a novel approach with regard to feature-based remote sensing image registration.There are two key contributions:1)we bring forward an improved strategy of composite nonlinear diffusion filtering according to the scale factors in multi-scale space and 2)we design a gradually decreasing resolution of multi-scale pyramid space.And a binary code string is served as feature descriptors to improve matching efficiency.Extensive experiments of different categories of remote image datasets on feature extraction and feature registration are performed.The experimental results demonstrate the superiority of our proposed scheme compared with other classical algorithms in terms of correct matching ratio,accuracy and computation efficiency.
