Depth extraction from 3D-integral images approached as an inverse problem

The paper presents two methods for the extraction of depth information from planar recorded data of 3D (three - dimensional) integral images. A description of the integral imaging system and the associated point spread function are presented. Depth estimation from 3D-integral pictures is formulated as an inverse problem of integral image formation. To cure the ill-posedness of the problem, approximate solutions are searched using so called dasiaregularization methodspsila. Two regularization schemes for obtaining constrained least-squares solutions are presented. The first algorithm is based on the projected Landweber method. The second method is a constrained version of Tikhonovpsilas regularization method for ill-posed problems. Finally, illustrative simulation results are given.