Improving Secondary Ion Mass Spectrometry Image Quality with Image Fusion

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• 作者：Jay G. Tarolli (1)
  Lauren M. Jackson (1)
  Nicholas Winograd (1)
  
• 关键词：SIMS ; Image processing ; Image fusion ; Algae ; Biofuels ; Botryococcus braunii
• 刊名：Journal of The American Society for Mass Spectrometry
• 出版年：2014
• 出版时间：December 2014
• 年：2014
• 卷：25
• 期：12
• 页码：2154-2162
• 全文大小：1,082 KB
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• 作者单位：Jay G. Tarolli (1)
  Lauren M. Jackson (1)
  Nicholas Winograd (1)
  
  1. Department of Chemistry, Pennsylvania State University, University Park, PA, 16802, USA
  
• ISSN：1879-1123

文摘

The spatial resolution of chemical images acquired with cluster secondary ion mass spectrometry (SIMS) is limited not only by the size of the probe utilized to create the images but also by detection sensitivity. As the probe size is reduced to below 1?μm, for example, a low signal in each pixel limits lateral resolution because of counting statistics considerations. Although it can be useful to implement numerical methods to mitigate this problem, here we investigate the use of image fusion to combine information from scanning electron microscope (SEM) data with chemically resolved SIMS images. The advantage of this approach is that the higher intensity and, hence, spatial resolution of the electron images can help to improve the quality of the SIMS images without sacrificing chemical specificity. Using a pan-sharpening algorithm, the method is illustrated using synthetic data, experimental data acquired from a metallic grid sample, and experimental data acquired from a lawn of algae cells. The results show that up to an order of magnitude increase in spatial resolution is possible to achieve. A cross-correlation metric is utilized for evaluating the reliability of the procedure. Figure ?/em>