![]() In this hybrid approach, the surface form is reconstructed by a deep learning model, while the prior calibration is performed by the conventional method using the simulation tool box SimOptDevice, , developed at the Physikalisch-Technische Bundesanstalt (PTB). Recent work, suggests the use of a deep learning hybrid approach to solve the inverse topography reconstruction problem. Measurement uncertainties are as yet not available for tilted-wave interferometry, but previous work addresses a number of relevant investigations,. Conventional TWI methods consist of three major steps for reconstructing the surface form: the prior correction of the interferometer model (“calibration”), , the reconstruction of the form deviation represented by Zernike polynomial functions and the reconstruction of the remaining high-frequency form deviations. The evaluation procedure of the TWI takes account of both measured data and simulated data, with the deviation of the specimen from its known design topography derived from the differences between the measured and simulated data, thus yielding a high-dimensional inverse problem. The tilted-wave interferometer (TWI), is one of the state-of-the-art interferometrical measurement techniques for optical form measurements of optical aspheres and freeform surfaces. In order to track the state-of-the-art in the form measurement of such optical surfaces, interlaboratory comparison studies are performed to analyze the differences between the various high accuracy measuring systems, including tactile and optical instruments. Non-spherical optics, like aspheres or freeform surfaces, are indispensable for modern optical systems. ![]() A manufactured good can be fabricated only as accurately as it can be measured. ![]() The need for accurate measurement techniques increases with ongoing technological advancements. ![]()
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