Disparity map generation, from the use of rectified images

In this paper, we propose the development of a system for generating disparity maps using rectified images, one technique that is booming in depth perception systems in computer vision. For this reason, in this project, is made a brief explanation process associated with mating techniques for stereo vision. For this project, we explore correlation algorithms, such as sum of absolute differences and Sum of Hamming Distances, combining the latter with the use of Census Transform. Additionally, we present the behavior of disparity maps for images that have been affected by impulsive noise. Initially rectified images were considered, which were taken from the image bank, presented by Middlebury College, who have worked extensively in the stereo vision problem. In this case, we used the known stereo pair Tsukuba.