Wavelet transform based optimization method for ThreeDimensional computer vision

Abstract

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.