13 June 2016 Fractal methods for extracting artificial objects from the unmanned aerial vehicle images
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J. of Applied Remote Sensing, 10(2), 025020 (2016). doi:10.1117/1.JRS.10.025020
Unmanned aerial vehicles (UAVs) have become used increasingly in earth surface observations, with a special interest put into automatic modes of environmental control and recognition of artificial objects. Fractal methods for image processing well detect the artificial objects in digital space images but were not applied previously to the UAV-produced imagery. Parameters of photography, on-board equipment, and image characteristics differ considerably for spacecrafts and UAVs. Therefore, methods that work properly with space images can produce different results for the UAVs. In this regard, testing the applicability of fractal methods for the UAV-produced images and determining the optimal range of parameters for these methods represent great interest. This research is dedicated to the solution of this problem. Specific features of the earth’s surface images produced with UAVs are described in the context of their interpretation and recognition. Fractal image processing methods for extracting artificial objects are described. The results of applying these methods to the UAV images are presented.
© 2016 Society of Photo-Optical Instrumentation Engineers (SPIE)
Eugene Markov, "Fractal methods for extracting artificial objects from the unmanned aerial vehicle images," Journal of Applied Remote Sensing 10(2), 025020 (13 June 2016). https://doi.org/10.1117/1.JRS.10.025020

Fractal analysis

Unmanned aerial vehicles


Image processing


Image resolution

Satellite imaging

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