The Bayesian Inference and Outliers Detection in Phototriangulation
نویسنده
چکیده
The Bayesian inference along with the step-by-step technique allows foresee a possibility to increase the efficiency and reliability of phototriangulation. It also appears to improve the strength of the block, in order to increase the economy with respect to control points. The used methodology consists on simulation of a 25 points mesh, from which a block of aerial photos is generated. Random and gross errors are added to the ideal photocoordinates. The LS adjustment, based on concept of Bayesian inference, is made. The Pope's method is used to detect and eliminate gross errors. The results show that for few outliers the approach works well; when the quantity increases the, efficiency decreases. By other hand, the better the quality of a priori parameters, the better the Z-coordinates of the object points.
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