首页> 外文期刊>Journal of Vacuum Science & Technology. B, Microelectronics and Nanometer Structures >Utilizing maximum likelihood deblurring algorithm to recover high frequency components of scanning electron microscopy images
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Utilizing maximum likelihood deblurring algorithm to recover high frequency components of scanning electron microscopy images

机译:利用最大似然去模糊算法恢复扫描电子显微镜图像的高频分量

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Applying an image deblurring technique used in image processing fields, scanning electron microscopy (SEM) images were enhanced by recovering the high frequency components of the image, thereby reducing image blur. The accuracy of the deblurring method was tested by examining isolated trenches, dense lines:trenches, and unpatterned photoresist. The images were artificially blurred, then deblurred. They were also rotated and compared. Any periodic structures on the image must have a pitch larger than the expected image blur. When that qualification is satisfied, a statistical confidence level far greater than 99% demonstrated that the method does indeed deblur properly and as desired. To some degree, the deblurring technique can be used to determine stage drift, aperture misalignment, astigmation, or other problems with the SEM that affect image blur.
机译:应用图像处理领域中使用的图像去模糊技术,通过恢复图像的高频成分来增强扫描电子显微镜(SEM)图像,从而减少图像模糊。通过检查隔离的沟槽,密集的线条:沟槽和未构图的光刻胶来测试去模糊方法的准确性。图像被人为地模糊,然后去模糊。他们也进行了轮换和比较。图像上的任何周期性结构的间距必须大于预期的图像模糊。当满足该条件时,远远超过99%的统计置信度表明该方法确实确实可以正确并按要求进行模糊处理。在某种程度上,去模糊技术可用于确定载物台漂移,孔径未对准,像散或影响图像模糊的SEM其他问题。

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