RESUMEN
Infrared scattering scanning near-field optical microscopy (IR s-SNOM) provides for spectroscopic imaging with nanometer spatial resolution, yet full spatio-spectral imaging is constrained by long measurement times. Here, we demonstrate the application of compressed sensing algorithms to achieve hyperspectral FTIR-based nano-imaging at an order of magnitude faster imaging speed to achieve the same spectral content compared to conventional approaches. At the example of the spectroscopy of a single vibrational resonance, we discuss the relationship of prior knowledge of sparseness of the employed Fourier base functions and sub-sampling. Compressed sensing nano-FTIR spectroscopy promises both rapid and sensitive chemical nano-imaging which is highly relevant in academic and industrial settings for fundamental and applied nano- and bio-materials research.
RESUMEN
Near-field goniometric measurements are employed to determine the photometric characteristics of light sources, i.e., the spatial and angular distribution of the emitted light. To this end, a complex measurement system consisting of a goniometer and a CCD-based imaging photometer is employed. In order to gain insight into the measurement system and to enable characterization of the whole measurement setup, we propose to apply a computer model to conduct virtual experiments. Within the computer model, the current state of all parts of the virtual experiment can be easily controlled. The reliability of the computer model is demonstrated by a comparison to actual measurement results. As an example for the application of the virtual experiment, we present an analysis of the impact of axial malpositions of the goniometer and camera.