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Nonwovens structure measurement based on NSST multi-focus image fusion

机译:基于NSST多焦点图像融合的非织造布结构测量

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摘要

In the digital optical microscope, the depth of field cannot clearly display all fibers in the same image, due to the thickness of nonwovens. A new multi-focus image fusion algorithm based on non-subsampled shearlet transform (NSST) is proposed to improve the quality of fused image, which realizes the fusion of a series of images taken from the same perspective and makes all fibers clearly within a single image. The rule of large absolute value is used to fuse the high frequency sub-band and the rule of large regional variance is used to fuse the low frequency sub-band. Comparing the method with other methods, the superiority of the method can be seen from several indicators of image quality evaluation. Based on the fused image, the diameter and orientation are measured by Hough transform and image preprocessing, and automatic measurement is realized. The porosity is measured by identifying pores, which is fast and convenient. Experiments show that the measurement of nonwoven fabric structure can be quickly achieved based on image processing.
机译:在数字光学显微镜中,由于非织造织物的厚度,景深不能清楚地显示相同图像中的所有光纤。提出了一种基于非撤销的Shearlet变换(NSST)的新的多聚焦图像融合算法,提高了融合图像的质量,这意味着从相同的角度拍摄的一系列图像的融合,并在单个纤维中清晰地制作所有光纤图片。大型绝对值的规则用于熔化高频子带,并且大区域方差规则用于熔断低频子带。将方法与其他方法进行比较,从图像质量评估的若干指标可以看出该方法的优越性。基于熔融图像,通过霍夫变换和图像预处理来测量直径和方向,并且实现自动测量。通过识别孔隙来测量孔隙率,这是快速方便的。实验表明,基于图像处理,可以快速实现非织造织物结构的测量。

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