Abstract
In stereo research the construction of a dense disparity map is a complicated task when the scene contains a lot of occlusions. In this case in the neighborhood of occlusions, we could consider that the images have a non-stationary behavior. In this paper we propose a new method for computing a dense disparity map using the decomposition of the 2D wavelet transform in four quarters allowing us to find a corresponding pixel in the case of occlusion as well. Our algorithm constructs in each pixel of two images four estimators corresponding to each quarter. The matching of the four wavelet coefficient estimators in the right image with the other four in the left image allow us to construct a dense map disparity map in each pixel of an image.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: International Journal of Pattern Recognition and Artificial Intelligence
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
