Accuracy enhanced and synthetic wavelength adjustable optical metrology via spectrally resolved digital holography

Flash-profilometry: fullfield lensless acquisition of spectral holograms for coherence scanning profilometry

Flash-profilometry is a novel measurement approach based on the fullfield lensless acquisition of spectral holograms. It is based on spectral sampling of the mutual coherence function and the subsequent calculation of its propagation along the optical axis several times the depth-of-field. Numerical propagation of the entire coherence function, rather than solely the complex amplitude, allows to digitally reproduce a complete scanning white-light interferometric (WLI) measurement. Hence, the corresponding 3D surface profiling system presented here achieves precision in the low nanometer range along an axial measurement range of several hundred micrometers. Due to the lensless setup, it is compact, immune against dispersion effects and lightweight. Additionally, because of the spectral sampling approach, it is faster than conventional coherence scanning WLI and robust against mechanical distortions, such as vibrations and rigid body movements. Flash-profilometry is therefore suitable for a wide range of applications, such as surface metrology, optical inspection, and material science and appears to be particularly suitable for a direct integration into production environments.

Terahertz pulse time-domain holography with balance detection: complex-domain sparse imaging

We investigated the peculiarities of the terahertz pulse time-domain holography principle in the case of raster scanning with the balance detection system. The noise in this system represents a Skellam distribution model, which differentiates it from systems based on a photoconductive antenna. We analyzed this Skellam model and provided both numerical and experimental investigations. We found that the variance of the noise in the balance detection system does not depend on the true signal. Complex-domain images obtained in this model are filtered by block-matching algorithms adapted for spatio-temporal and spatiospectral volumetric data. We presented a new cube complex-domain filter algorithm that uses block matching in all 3D data sets simultaneously in spatial and frequency coordinates. A combination of temporal and complex-domain filters allows us to expand the dynamic range of terahertz frequencies for which we can obtain amplitude/phase information. Experimental data demonstrate an improvement in the quality of the resultant images both in the time domain and complex-spectral domain. The simulation and experimental results are in good agreement.

Spectral Object Recognition in Hyperspectral Holography with Complex-Domain Denoising

In this paper, we have applied a recently developed complex-domain hyperspectral denoiser for the object recognition task, which is performed by the correlation analysis of investigated objects’ spectra with the fingerprint spectra from the same object. Extensive experiments carried out on noisy data from digital hyperspectral holography demonstrate a significant enhancement of the recognition accuracy of signals masked by noise, when the advanced noise suppression is applied.

Hyperspectral data denoising for terahertz pulse time-domain holography

We investigated data denoising in hyperspectral terahertz pulse time-domain holography. Using the block-matching algorithms adapted for spatio-temporal and spatio-spectral volumetric data we studied and optimized parameters of these algorithms to improve phase image reconstruction quality. We propose a sequential application of the two algorithms oriented on work in temporal and spectral domains. Experimental data demonstrate the improvement in the quality of the resultant time-domain images as well as phase images and object's relief. The simulation results are proved by comparison with the experimental ones.