Abstract
Aiming at the problem of missing data after point cloud data filtering, this paper proposes a point cloud repair method based on the principle of Linear Maximum Entropy, which converts the Maximum Entropy Model into a linear model, and then uses linear programming to solve the model. The mathematical expectation and variance in the elevation value is used to establish linear constraints, and the weight coefficient of the sampling point is solved by the maximum entropy value to determine the elevation value of the fixed point, so as to complete the point cloud repair. By comparing with Maximum Entropy Method and Inverse Distance Weight method, the feasibility of Linear Maximum Entropy Model in point cloud data repairs is discussed. The results show that the point cloud data repaired by the Linear Maximum Entropy Model is more accurate, and a high-quality model can be established.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
