Аннотация:
This work aims to develop approximate depth estimation methods for three-dimensional computer vision
in unmanned vehicles (UVs) based on a developed wavelet transformation-based optimization method. This
method can assess informative features for matching and/or optimizing costs in image analysis, refining
discrepancies, and more. Possible solutions are demonstrated for obtaining an approximate depth map by
simplifying the calculation of disparity values, traditionally used for forming a depth map in intensity space
and using edge description with adjustable detail based on wavelet transformation. The advantage of the
developed optimization method over existing algorithms in the wavelet space is the increased speed due to
the rational selection of the Haar wavelet support length in the extremum search area. Modeling confirmed
the effectiveness of the proposed approach for constructing depth maps and allowed for recommending the
proposed method for unmanned vehicles operating under limited computational and energy resources.
