Abstract
Window-based correlation algorithms are widely used for stereo matching due to their computational efficiency as compared to global algorithms. In this paper, a multiple window correlation algorithm for stereo matching is presented which addresses the problems associated with a fixed window size. The developed algorithm differs from the previous multiple window algorithms by introducing a reliability test to select the most reliable window among multiple windows of increasing sizes. This ensures that at least one window is large enough to cover a region of adequate intensity variations while at the same time small enough to cover a constant depth region. A recursive computation procedure is also used to allow a computationally efficient implementation of the algorithm. The outcome obtained from a standard set of images with known disparity maps shows that the generated disparity maps are more accurate as compared to two popular stereo matching local algorithms.
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 callDisclaimer: 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.
