An Improved Binary Particle Swarm Optimization of RFM’s for ALSAT2 Imagery

dc.contributor.authorMezouar , Oussama
dc.contributor.authorMeskine, Fatiha
dc.contributor.authorBoukerch, Issam
dc.date.accessioned2024-03-12T17:17:13Z
dc.date.available2024-03-12T17:17:13Z
dc.date.issued2021-05-25
dc.description.abstractRational function model (RFM) is commonly used in photogrammetric and remote sensing applications because it does not need sensor parameters. Therefore, the RFM terms or also rational polynomial coefficients (RPCs) have no physical significance but depends on many ground control points (GCPs) that make the model prone to the over parameterization problem. This paper proposes a new binary particle swarm optimization algorithm to surmount the issue of over parameterization and find the optimum combination of RPCs for the RFM by adding a new transfer function in binary PSO in order to increase the convergence speed and avoid the local minimum phenomenon. The results showed that the proposed method is compatible with different types of RFM, more stable, and gives higher accuracy than the traditional binary PSO.
dc.identifier.isbn978-9931-9788-0-0
dc.identifier.urihttp://dspace.univ-oeb.dz:4000/handle/123456789/18716
dc.language.isoen
dc.publisherUniversity of Oum El Bouaghi
dc.subjectRational function model; particle swarm optimization; Ortho-rectification; meta-heuristic; high-resolution satellite images
dc.titleAn Improved Binary Particle Swarm Optimization of RFM’s for ALSAT2 Imagery
dc.typeArticle
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