一种散斑模式的噪声统计模型与自适应滤波方法

本文介绍了一种实际散斑模式的数学模型和噪声统计模型，并提出了一种针对这种模型的自适应次优滤波方法。文中在分析了散斑模式及其噪声性质的基础上，利用其局部方向性特征，结合最优线性滤波器和非线性滤波器的特点，对线性最小均方误差滤波器进行了自适应逼近，实验结果表明，对散斑模式而言，本文的滤波方法与其它常用的图象滤波方法相比，具有更好的去噪和边缘保护性能，并且具有较好的滤波韧性。     

A STATISTICAL NOISE MODEL AND MATHEMATICAL MODEL OF SPECKLE PATTERN AND ADAPTIVE FILTERING APPROACH

A statistical noise model and a mathematical model for real speckle pattern are presented in this paper, and then, in view of the models, a new adaptive suboptimal image filtering approach is proposed. The proposed approach, with the local direction features of speckle pattern, combines the characteristics of optimal linear filter with non-linear filter and is an adaptive approximation to linear minimum mean square error filter. Experimental results show that the proposed approach has fairly good edge-preserved performance, compared with other present image filters, as well as much better filtering performance and robustness for speckle pattern.     

一种散斑模式的噪声统计模型与自适应滤波方法

本文介绍了一种实际散斑模式的数学模型和噪声统计模型,并提出了一种针对这种模型的自适应次优滤波方法。文中在分析了散斑模式及其噪声性质的基础上,利用其局部方向性特征,结合最优线性滤波器和非线性滤波器的特点,对线性最小均方误差滤波器进行了自适应逼近。实验结果表明,对散斑模式而言,本文的滤波方法与其它常用的图象滤波方法相比,具有更好的去噪和边缘保护性能,并且具有较好的滤波韧性。