Abstract
Abstract—The representation of spatially inhomogeneous images using double stochastic autoregressive models is considered. The possibility of synthesizing semicausal double stochastic image filtering algorithms based on such models is shown. Variants for reducing the computational costs required to implement double stochastic filters using cascades of moving windows are considered. A comparative analysis of the proposed algorithms with well-known counterparts is carried out, confirming the practical possibility of using double stochastic filters for processing real two-dimensional images.
Published Version
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: Journal of Communications Technology and Electronics
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.
