Abstract

In order to overcome the disadvantages of poor global search ability, slow convergence speed and easy to fall into local minimum in the traditional BP neural network in image denoising, a hybrid ACO-LMBP neural network image denoising algorithm based on ant colony algorithm and LMBP algorithm is proposed. ACO-LMBP hybrid neural network algorithm has both the high speed of LMBP algorithm and the global nature of ACO algorithm. It can improve the problems of BP algorithm model very well. By comparing with the image denoising effect of Wiener filtering, BP, LMBP and PSO-LMBP model, the denoising model using the ACO-LMBP neural network algorithm has better denoising effect.

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 call

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.