Abstract

Image noise is mainly introduced in the process of image imaging. Different imaging mechanisms lead to different distribution characteristics of image noise. The maximum likelihood method is a commonly used parameter estimation method, which can obtain a good estimation effect for Gaussian distribution, but it has the disadvantage of relatively complicated calculation when it is used for parameter estimation of mixed Gaussian distribution. However, it has the disadvantage of relatively complicated calculation when it is used for parameter estimation of mixed Gaussian distribution. The EMs of this paper flexibly bring their blurring effects. The solution of the maximum likelihood equation is simplified by introducing potential variables, which has the advantages of smooth implementation of equations, stable numerical calculation, and guaranteed convergence to a stable point to make up for the deficiency of the maximum likelihood method

Full Text
Paper version not known

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.