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A New Wave-Front Reconstruction Method for Adaptive Optics Systems Using Wavelets

机译:基于小波的自适应光学系统波前重构新方法

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ara> A new technique for wave-front reconstruction from gradient measurements on a square data set is presented. This technique is based on obtaining the Haar wavelet image decomposition of the original wave-front by appropriate filtering and down-sampling of the gradient measurement data. The use of the wavelet decomposition leads to an algorithm with complexity of $O(N)$, where N is the number of data points in the reconstruction, and at the same time allows denoising of the data using the wavelet coefficients. The proposed technique is illustrated with two examples and its reconstruction accuracy, computational speed and denoising performance are discussed. Results indicate that the proposed technique is a computationally efficient and accurate technique for wave-front and/or image reconstruction from gradient measurements.
机译:ara>提出了一种从平方数据集上的梯度测量中进行波前重建的新技术。该技术基于对梯度测量数据进行适当的滤波和下采样,从而获得原始波前的Haar小波图像分解。小波分解的使用导致算法的复杂度为 $ O(N)$ ,其中N是数据点在重建中,同时允许使用小波系数对数据进行去噪。通过两个实例对提出的技术进行了说明,并讨论了其重构精度,计算速度和降噪性能。结果表明,所提出的技术是一种用于从梯度测量中重建波前和/或图像的计算有效且准确的技术。

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