基于泊松-高斯混合噪声的最大似然改进算法

Modified Maximum Likelihood Algorithm Based on Poisson-Gaussian Mixed Noise

传统的图像复原算法仅针对高斯噪声进行处理,没有考虑高斯及泊松混合噪声污染。为此,引入泊松-高斯混合分布的成像模型,对基于混合模型的最大似然算法进行有效近似,在此基础上提出基于泊松-高斯混合噪声的最大似然改进算法,避免对噪声敏感性和PSF初始估计的依赖。实验结果表明,与原有算法相比,改进算法复原效果明显,且稳健性较好。

Traditional image restoration algorithms always deal with Gaussian noise,however,the real astronomical images are polluted by Gaussian and Poisson mixed noise.Therefore,this paper introduces a imaging model of Poisson-Gaussian distribution,makes an effective approximation to the Maximum Likelihood（ML） algorithm based on the mixed model,and proposes a modified ML algorithm based on Poisson-Gaussian mixed noise to avoid the sensitivity to noise and the dependence to the original estimation of PSF.Experimental results show that this algorithm works well,and the robustness is well.