Description: Working with aerospace images it is a necessary stage to define spatial coordinates of the objects in the image. Analysis of the works in that field has shown that the currently available image processing algorithms are quite thoroughly worked through for spatial and high-altitude aerial imaging data, but those algorithms do not take into account specificity of the data, acquired by unmanned aerial vehicles (UAV), namely low flight altitude and as a consequence small surveillance area; absence of gyroscope reference platform for ‘mini’ and ‘micro’ UAVs; lack of synchronization between the moment of imaging and derivation of the aircraft’s spatial position and angles; poor accuracy of determination of imaging instruments external orientation elements; imaging instruments movement and vibration; stochastic excitations caused by endoatmosphere that result in considerable distortion of perspective in the image. That is the reason why the problem of adapting the existing algorithms and developing new algorithms for geographical referencing of the images received by UAVs becomes critical. The problem of referencing images received by UAVs with the usage of approximating functions is the presence of serious perspective distortions, small scene area in the frame, that results in impossibility to specify due number of defining points in the image for achieving high precision. At solving the task of photogrammetric processing by classical methods it is impossible to correct external orientation elements with the usage of Taylor series because of insufficient accuracy of initial approximations. The method considered in the paper uses simplex method of deformed polygon and allows restoring true values of external orientation elements that are further used for deriving geographical coordinates of a point in the image.
Keywords: images coordinate referencing, external orientation elements, approximating functions, triangulation network, simplex method of deformed polygon