Unscented Kalman Filter for Image Estimation in Film-Grain Noise
Unscented Kalman Filter for Image Estimation in Film-Grain Noise
复制标题
用于胶片颗粒噪声中图像估计的无迹卡尔曼滤波器
DOI：
10.1109/icip.2007.4379942
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发表时间：
2007
期刊：
影响因子：
--
通讯作者：
R. Aravind
中科院分区：
文献类型：
--
作者：
G. R. S. Subrahmanyam;A. Rajagopalan;R. Aravind
提出了一种基于无迹卡尔曼滤波(UKF)的胶片颗粒噪声图像估计新方法。图像先验被建模为非高斯，并使用重要性采样将其合并到UKF框架中。一组精心选择的确定的小西格玛点被用来捕捉先验信息，并通过胶片颗粒的非线性传播来计算图像统计量。实验结果证明了该方法的有效性。
This paper presents a novel approach based on the unscented Kalman filter (UKF) for image estimation in film-grain noise. The image prior is modeled as non-Gaussian and is incorporated within the UKF frame work using importance sampling. A small carefully chosen deterministic set of sigma points is used to capture the prior and is propagated through film-grain nonlinearity to compute image statistics. Experimental results are given to demonstrate the efficacy of the proposed method.