Digital holography (DH) is capable of providing three-dimensional topological surface profiles with axial resolutions in the nanometer range. To achieve such high resolutions requires an analysis of the phase information of the reflected light by means of numerical reconstruction methods. Unfortunately, the phase analysis of structures located in scattering media is usually disturbed by interference with reflected light from different depths. In contrast, low-coherence interferometry and optical coherence tomography (OCT) use broadband light sources to investigate the sample with a coherence gate providing tomographic measurements in scattering samples with a poorer depth-resolution of a few micrometers. We propose a new approach that allows recovering the phase information even through scattering media. The approach combines both techniques by creating synthesized interference patterns from scanned spectra. After applying an inverse Fourier transform to each spectrum, we yield three-dimensional depth-resolved images. Subsequently, contributions of photons scattered from unwanted regions are suppressed by depth-filtering. The back-transformed data can be considered as multiple synthesized holograms and the corresponding phase information can be extracted directly from the depthfiltered spectra. We used this approach to record and reconstruct holograms of a reflective surface through a scattering layer. Our results demonstrate a proof-of-principle, as the quantitative phase-profile could be recovered and effectively separated from scattering influences. Moreover, additional processing steps could pave the way to further applications, i.e. spectroscopic analysis.
We use Spectroscopic Optical Coherence Tomography (S-OCT) to identify substances by their spectral features in multi
layer non-scattering samples. Depth resolved spectra are calculated by a windowed Fourier Transform in the spatial
regime at discrete layer borders. By dividing subsequent spectra in an iterative manner transfer functions of the samples
layers are calculated. Estimating these spectral transfer functions with high accuracy is still challenging, since the
system´s transfer function introduces an error, which can be orders of magnitude higher than the spectroscopic
information of the sample. We retrieve the buried spectroscopic information of the sample with high accuracy by
correcting the spectral transfer functions with an identically structured reference sample. This spectral calibration method
has many critical parameters and is in many cases not even possible. To perform substance identification without spectral
calibration we implemented a pattern recognition algorithm, which allocates the transfer functions to known substances.
Our results show that substance identification by spectral features with high performance without spectral calibration is
feasible. Aside from that we modeled a simplified set up of our OCT system to minimize the error which is introduced
by the optical system. The error can be reduced by orders of magnitude, when our improved optical set-up is used. This
is an important step towards an improved system for S-OCT.