摘要: 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。
关键词:
图像复原,
泊松-高斯混合噪声,
最大似然算法,
TV去噪,
自适应参数估计
Abstract: 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.
Key words:
image restoration,
Poisson-Gaussian mixed noise,
Maximum Likelihood(ML) algorithm,
TV denoising,
adaptive parameter estimation
中图分类号:
魏小峰, 耿则勋, 宋向, 王洛飞, 唐橙. 基于泊松-高斯混合噪声的最大似然改进算法[J]. 计算机工程, 2012, 38(01): 222-224.
WEI Xiao-Feng, GENG Ze-Xun, SONG Xiang, WANG Luo-Fei, TANG Chen. Modified Maximum Likelihood Algorithm Based on Poisson-Gaussian Mixed Noise[J]. Computer Engineering, 2012, 38(01): 222-224.