Abstract

The estimation of the depth of a scene has become a research niche due to the large number of applications that exist today. In a stereo vision system, disparity maps make it possible to obtain the depth of a scene from two rectified images. Stereo vision systems are sensitive to illumination, reflections, lens distortion, noise, camera alignment, etc.; therefore, in this work, we present an algorithm that allows us to improve the disparity map when the environment presents particles in suspension using stereo vision through infrared cameras. For this purpose, filters, matching, and dehazing algorithms are implemented.