Fringe pattern denoising is of prime importance in phase demodulation, especially for a single fringe pattern in speckle interferometry. A fringe speckle noise removal algorithm using the Kalman filter is proposed. The conventional linear Kalman filter is implemented with a fixed value of the process and measurement noise covariances; the adaptive Kalman filter is implemented with the process, and measurement noise covariances are estimated in an adaptive manner. The fringe denoising is performed sequentially in a rowwise and columnwise manner. The simulated and experimental results demonstrate the practical applicability of the proposed method, and its performance is appraised using metrics such as the quality index, peak signal-to-noise-ratio, and speckle index.

中文翻译：

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使用自适应卡尔曼滤波器降低散斑干涉条纹图案的噪声

条纹图案去噪在相位解调中至关重要，特别是对于散斑干涉测量中的单个条纹图案。提出了一种基于卡尔曼滤波器的条纹散斑噪声去除算法。传统的线性卡尔曼滤波器是用固定值的过程和测量噪声协方差来实现的；自适应卡尔曼滤波器与该过程一起实现，并以自适应方式估计测量噪声协方差。条纹去噪按行列方式依次进行。仿真和实验结果证明了该方法的实际适用性，并使用质量指数、峰值信噪比和散斑指数等指标对其性能进行了评估。