Abstract
This work presents a new Markov random field (MRF) framework for image segmentation by incorporating exact contexts in the label field as well as the observed data. On the one hand, the new framework presents MRF with adaptive neighborhood (MRF-AN) system to model adaptively the contextual information of the hidden label field. On the other hand, the new framework models observations via a conditional random field (CRF), which incorporates the contextual information in observed data. The new MRF framework with the dual adaptive contextual information offers several advantages over the conventional framework. In this work, we demonstrate the advantages in an application of detail preservation in image segmentation.
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.
