Enhanced Axial Localization of Rough Objects Using Statistical Fringe Processing Algorithm

摘要

Fringe patterns carry valuable spatio-temporal information about the object being investigated. Fringe processing, however, is hampered by the presence of speckle noise which is a by-product of coherent metrology of optically rough surfaces. A speckle noise-robust fringe processing algorithm we developed based on the statistical properties of fringe patterns is revisited. The algorithm evaluates the change in the standard deviation of fringe patterns yielding a 2-D contrast map of spatial frequencies along the transverse directions. Application of the algorithm along the axial direction has not been reported. Here a technique for enhanced axial localization of rough test objects based on the statistical fringe processing algorithm is demonstrated experimentally. The main advantages of the localization technique are robustness against speckle noise and high axial resolution in the range of the light source wavelength.