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Autofocus algorithm based on Wavelet Packet Transform for infrared microscopy

机译:基于小波包变换的红外显微自动聚焦算法

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A new autofocus algorithm based on Wavelet Packet Transform (WPT) was presented to find the best focus of infrared microscopy, which is applied to test the defocusing amounts of athermalized infrared optical system. According to the statistical analysis of the gradient of image, the focus function was obtained by weighting the decomposition coefficients of wavelet packet. Experimental results demonstrated the algorithm had high sensitivity and accuracy for the true focus position from a series of infrared images. Furthermore, the autofocus algorithm was compared with some well-know algorithm like the Sobel Gradient(SG), the Sum-Modified Laplacian(SML) and the Discrete Cosine Transform(DCT) method in order to prove its performance.
机译:提出了一种基于小波包变换(WPT)的自动聚焦算法,以寻找红外显微镜的最佳聚焦点,并将其应用于测试热红外光学系统的散焦量。通过对图像梯度的统计分析,对小波包的分解系数进行加权,得到聚焦函数。实验结果表明,该算法对一系列红外图像的真实聚焦位置具有很高的灵敏度和准确性。此外,将自动对焦算法与Sobel Gradient(SG),Sum-Modified Laplacian(SML)和Discrete Cosine Transform(DCT)方法等知名算法进行了比较,以证明其性能。

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