“…There are several known ways to partially solve the problem of limited spatial resolution. They include the following hardware and algorithmic directions: • structural improvements (Popov et al, 2015;Popov, 2018), application of multicamera photographic devices (The largest, 2021) (but they complicate the observation device design); • reduction of elementary receiver size to the diffraction limit while is increasing of number of such receivers in a photosensitive matrix (OWC, 2021; Rehm, 2021) (unfortunately, their realization is technologically difficult and they are limited by theoretical limits of applicability); • taking into account in the design of the receiver tasks for the observation of objects with a finite size of object recognition (Korobchynskyi et al, 2020) (but it is not always possible to predict in advance the required depth of object recognition by its image); • using the features of zonal images of the object and its components (Popov et al, 2007;Ferraris et al, 2018) (at hyperspectral observation of the object is accumulated a huge amount of information, its interpretation requires high and specific qualification of the operator); • application of neural network technologies, algorithms of extrapolation, interpolation, probabilistic analysis and estimation (Kwan, 2018;Stankevich et al, 2020) (it is a very promising areas, which are based on the use of a priori information like the results of observation and documentation of the observation device).…”