1. Increasing the spatial resolution of near infrared chemical images (NIR-CI): The super-resolution paradigm applied to pharmaceutical products
- Author
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Yves Roggo, Marc Offroy, Ludovic Duponchel, Laboratoire Avancé de Spectroscopie pour les Intéractions la Réactivité et l'Environnement - UMR 8516 (LASIRE), Institut de Chimie du CNRS (INC)-Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Centrale Lille Institut (CLIL), F. Hoffmann-La Roche A.G., Switzerland, and Institut de Chimie du CNRS (INC)-Université de Lille-Centre National de la Recherche Scientifique (CNRS)
- Subjects
Chemical imaging ,Computer science ,Nanotechnology ,Field of view ,02 engineering and technology ,01 natural sciences ,Imaging ,Analytical Chemistry ,Chemometrics ,0202 electrical engineering, electronic engineering, information engineering ,Image resolution ,NIR-CI ,Spectroscopy ,Remote sensing ,Process Chemistry and Technology ,010401 analytical chemistry ,Near-infrared spectroscopy ,Detector ,Sample (graphics) ,0104 chemical sciences ,Computer Science Applications ,Characterization (materials science) ,[CHIM.THEO]Chemical Sciences/Theoretical and/or physical chemistry ,Super-resolution ,020201 artificial intelligence & image processing ,Pharmaceutical products ,Powders ,Software ,Tablets - 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.
- Published
- 2012
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