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Autofocus algorithm based on Wavelet Packet Transform for infrared microscopy

机译:基于小波包变换的自动对焦算法用于红外显微镜

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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)的新型自动对焦算法,以找到红外显微镜的最佳焦点,用于测试灰尘化红外光学系统的散焦量。根据图像梯度的统计分析,通过加权小波包的分解系数来获得焦点函数。实验结果表明,该算法对来自一系列红外图像的真正焦点位置具有高灵敏度和准确性。此外,将自动对焦算法与Sobel梯度(SG),Sum修改的Laplacian(SML)和离散余弦变换(DCT)方法进行了比较,以便证明其性能。

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