Sim K-S, Tso C-P, Law K-K
Faculty of Engineering and Technology, Multimedia University, Melaka, Malaysia.
Microsc Res Tech. 2008 Apr;71(4):315-24. doi: 10.1002/jemt.20558.
The mixed Lagrange time-delay estimation autoregressive (MLTDEAR) model is proposed as a solution to estimate image noise variance. The only information available to the proposed estimator is a corrupted image and the nature of additive white noise. The image autocorrelation function is calculated and used to obtain the MLTDEAR model coefficients; the relationship between the MLTDEAR and linear prediction models is utilized to estimate the model coefficients. The forward-backward prediction is then used to obtain the predictor coefficients; the MLTDEAR model coefficients and prior samples of zero-offset autocorrelation values are next used to predict the power of the noise-free image. Furthermore, the fundamental performance limit of the signal and noise estimation, as derived from the Cramer-Rao inequality, is presented.
提出了混合拉格朗日时滞估计自回归（MLTDEAR）模型来估计图像噪声方差。所提出的估计器可用的唯一信息是一幅受损图像和加性白噪声的性质。计算图像自相关函数并用于获得MLTDEAR模型系数；利用MLTDEAR与线性预测模型之间的关系来估计模型系数。然后使用前后向预测来获得预测器系数；接下来使用MLTDEAR模型系数和零偏移自相关值的先验样本预测无噪声图像的功率。此外，还给出了从克拉美-罗不等式推导得出的信号与噪声估计的基本性能极限。
