Quantitative Data Analysis for Electron Microscopy
Abstract: Electron microscope magnifies an object and exposes fine structures before the naked eyes. Therefore, a great deal of effort has been put into getting an improved data by inventing a new technique of observation or by improving an instrument. On the other hand, useful information that cannot be recognized by just looking a raw data may be obtained by processing the raw data. However, data processing should not create information that does not exist in the original data. In this report I would like to introduce some beneficial image processing techniques that extract information in the data to be recognized by human being. Such a processing is a kind of double-edged sword, however, and a deep knowledge on the object will be required to correctly explain the result. I hope many of clever readers of this article will try such data processing to tackle their difficult problem.
Key words: Wiener Filter, Deconvolution, Maximum Entropy Method, Richardson-Lucy Algorithm, Strain Analysis