Adaptive statistical filtering of data in the phase images decoding under random additive noise of a photodetector

Abstract

A method for adaptive statistical filtering of experimental data is proposed to reduce the measurement error of three-dimensional geometric parameters using phase triangulation methods. The method is especially promising for use under conditions of measuring surfaces with random light-scattering properties, a limited dynamic range of a photodetector, and random additive noise. The practical value and efficiency of the proposed approach in the processing of phase images is shown.