Chromatic confocal spectral interferometry (CCSI)

Chromatic Confocal Spectral Interferometry (CCSI) is a hybrid measurement principle for 3D topometry without the need for axial scanning. CCSI benefits from the precision of interferometric principles as well as the robustness of confocal microscopy, while avoiding most of their individual shortcomings. Based on axial separation of foci and spectral detection of a white-light signal, it provides single-shot measurements.

For Spectral Interferometry (SI), measurement range is limited by the depth of focus of the microscope objective. As depth of focus, as well as lateral resolution, are depending on the numerical aperture of the system, there is always a tradeoff between large measurement range and high lateral resolution. By chromatic separation and confocal filtering, CCSI overcomes this link. This enables a sensor, which combines high lateral resolution and large axial measurement range.

In addition to the CCSI sensor mentioned before, which are single-shot point sensors, the concept of combining SI and chromatic encoding was transferred to a line sensor design. Each point of the line gets illuminated by a specific wavelength. Therefore the spectral signal encodes the object height of each illuminated point as well as its position.

Signal evaluation for CCSI

One of the main advantages of CCSI is that the axial position of the object is encoded in both, confocal envelope and interferometric wavelet. In contrast to scanning white light interferometry, both information channels are intrinsicly decoupled, yielding robust evaluation strategies. The confocal enveloped can be assessed by a simple center-of-gravity calculation. But the resolution is limited to that of confocal microscopy and also the known artifacts are present in the result. However, the interferometric information provides much higher resolution, but fails on discontinuities or steep gradients. Fig. 1 shows a comparison of both evaluation methods (Fig. 1a), as well as the results of a combined algorithm, that uses both evaluation paths and therefore provides a more robust evaluation (Fig. 1b).


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