Chromatic confocal spectral interferometry combines the benefits of scanning free acquisition of the axial dimension with interferometrically increased depth accuracy. However, so far it has been difficult to separate the confocal signal from the interferometric signal. It is, of course, possible to apply the established CCM evaluation methods. In that case, the available phase information, that offers a decreased measurement uncertainty and to some degree the removal of disturbing artifacts at steep surface inclinations, is not taken into account. In fact, it is not straight forward to interpret the signal. In comparison to white light interference microscopy, the signal suffers from a chirp. This means that it cannot be associated with a single beating frequency, which corresponds to the interferometrically encoded z-value. However, a modified lock-in technique has in the past successfully been applied, demonstrating a significant advantage in comparison to the conventional CCM procedures. Here, we will introduce the concept of k-space phase equality, which enables the separation of the confocal and the interferometric signal and furthermore offers an extended measurement range. The principle is based on signal modification in the z-space, which corresponds to the Fourier domain of the recorded spectral signal. The evaluation is then performed in the spectral domain, where the phase signals for all z-positions with respect to the corresponding wavelength are evaluated. As a result, a phase signal with reduced aberration terms, similar to an interferometric signal, is obtained, which can hence be evaluated using established techniques.
Traditional spectral unmixing involves intense signal processing applied on multispectral or hyperspectral data captured from an imaging device, which is highly time-consuming. In this article, a novel method, namely "optical unmixing", is proposed to alleviate the post processing effort by replacing the heavy computation with a spectrally tunable light source. By choosing spectral features of the light source intelligently, the abundance map of each material can be retrieved with minimum computation from gray value images captured by a normal camera. For n unknown endmembers, 3n + 1 measurements are required to retrieve the abundance maps with proposed algorithms.
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