Abstract
Near-infrared chemical imaging (NIR-CI) is widely used in the pharmaceutical industry not only to provide the concentration of a compound of interest but far more often to obtain the spatial distribution of different ingredients within the considered sample like a single tablet. For such sample characterization, having a high field of view is of major interest. As well as their high field of view, recent NIR-CI spectrometers have the ability to acquire thousands of spectra in a very short time due to focal plane array detector they use. Nevertheless, the spatial resolution is often limited which implies that generated chemical images are often biased. In view of this it was deemed appropriate to develop a new chemometrics methodology called “super-resolution” in order to increase the spatial resolution of spectroscopic images. The main idea is the fusion of several low-resolution images of the same sample observed from different point of view in order to generate one higher-resolution image. We offer here an objective and quantitative evaluation of the super-resolution concept with applications on pharmaceutical solid samples.
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