An approximate method of estimating the depth of objects using wavelet-based transformation

Modern three-dimensional computer vision technologies are actively developing, offering new solutions based on the analysis of environmental details. One of the key tasks is to determine the depth of location of objects in images, which requires efficient and fast methods of their processing. This study proposes a new depth estimation method for 3D computer vision based on wavelet transform optimization. Solutions are offered to simplify the disparity calculation, which is traditionally used for the construction of depth maps, with the possibility of describing contours with adjustable detail based on the wavelet transform. The main advantage of this method is the increase in performance due to the allocation of the Haar wavelet carrier length in the extremum search area. The simulation confirmed the effectiveness of the proposed approach for constructing depth maps, which allows us to recommend it for use in unmanned aerial vehicles (UAVs) in conditions of limited computing and energy resources.