internal displacement measurement. Abstract. In the field of experimental mechanics, there exist some circumstances when only data at the boundary can be obtained while the internal data are unavailable, or when some data are missed due to shadow, illumination saturation and other reasons. Thus it would be helpful if a reasonable estimation of the unavailable or missed data can be obtained. In this study, an algorithm is developed to reconstruct the missed data from the existing ones by generating a series of equations about the missed data and solving for an optimal solution using least-squares approach. Results based on both simulation data and real incomplete experimental data obtained by shearography and fringe projection show the usefulness and potential of the algorithm for experimental mechanics applications. Image reconstruction is a broad sense term. Some researchers refer it to “inpainting ” problem where some missed areas in an image are restored using Bayesian and variational principles based on the statistic properties of the intact areas [1-3]. A more majority of researchers in the fields of computer tomography (CT), magnetic resonance and radar astronomy use this term to describe the problem of