Abstract
Pulse coupled neural networks (PCNN) model is a bionic system. It emulates the behavior of visual cortical neurons of cats and has been extensively applied in image processing. A modified PCNN model was designed in the filter proposed for mixed-noise removal. The filter consists of two stages. The first stage smoothes small-amplitude Gaussian-noise and detects impulse noise or large-amplitude Gaussian-noise by a modified PCNN model, which uses a linear- attenuate threshold function and outputs weighted-averaging intensities of firing pixels, so it is abbreviated as L&A-PCNN. The second stage uses median filter to recover those detected noises. Setting parameters of the PCNN model is critical in designing an ideal filter, so the parameters of L&A-PCNN model are analyzed and adapt to suit the improvement. Simulation experiments show the advantage of the proposed approach.
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.
