Improvement of least-squares integration method with iterative compensations in fringe reflectometry

Abstract

Least-squares integration is one of the most effective and widely used methods for shape reconstruction from gradient data, which result from gradient measurement techniques. However, its reconstruction accuracy is limited due to the imperfection of the Southwell grid model, which is commonly applied in the least-squares integration method. An operation with iterative compensations is therefore proposed, especially for the traditional least-squares integration method, to improve its integration accuracy. Simulation and experiment are carried out to verify the feasibility and superiority of the proposed operation. This compensatory operation with iterations is suggested, and its good performance on integration accuracy improvement is shown.