Multi-Frame Star Image Denoising Algorithm Based on Deep Reinforcement Learning and Mixed Poisson–Gaussian Likelihood
Mixed Poisson–Gaussian noise exists in the star images and is difficult to be effectively suppressed via maximum likelihood estimation (MLE) method due to its complicated likelihood function. In this article, the MLE method is incorporated with a state-of-the-art machine learning algorithm in order...
Main Authors: | Ming Xie, Zhenduo Zhang, Wenbo Zheng, Ying Li, Kai Cao |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2020-10-01
|
Series: | Sensors |
Subjects: | |
Online Access: | https://www.mdpi.com/1424-8220/20/21/5983 |
Similar Items
-
Quantitative Reconstruction and Denoising Method HyBER for Hyperspectral Image Data and Its Application to CRISM
by: Linyun He, et al.
Published: (2019-01-01) -
Pseudo-Poisson Distributions with Concomitant Variables
by: Barry C. Arnold, et al.
Published: (2023-01-01) -
A Comparison Between Estimating The Parameters of The Gaussian Process Regression Model Using The Maximum Likelihood and The Restricted Maximum Likelihood Methods
by: Amena ilyas, et al.
Published: (2024-12-01) -
Explicit Gaussian Variational Approximation for the Poisson Lognormal Mixed Model
by: Xiaoping Shi, et al.
Published: (2022-12-01) -
Modified signed log-likelihood test for the coefficient of variation of an inverse Gaussian population
by: Mohammad Reza Kazemi
Published: (2022-03-01)