A novel model for building information acquisition optimization technology of remote sensing observation

It is an important problem in remote sensing that using limited observing points acquire the maximum quantity of building information. In this paper, a building information acquisition (BIA) model based on Support Vector Machine (SVM) is proposed for quantitative description of the mathematical relationship between the information quantity acquisition and the observing angles, which is optimized to obtain the maximum information quantity in the multi-temporal remote sensing observation. The main idea of the BIA model is that, to calculate information quantity at different observing angles, the target is decomposed into multiple faces whose information is described by the combined vector. Further, the modified bee colony algorithm is utilized to optimize the model to achieve the ideal maximum information quantity. The corresponding combined vector is optimal observing angles combination. The proposed model method performs well in our imaging simulation system data. Experiment results demonstrate that the proposed BIA model optimized will provide much more information quantity than observing randomly.