Fidelity tolerance analysis for computational imaging system

Abstract

Computational imaging has been using for depth of field extension, distance estimation and depth map for stereo imaging and displaying with great successfully, which are realized by using special designed imaging lens and optimized image post-processing algorithm. Several special coding structures have been presented, like cubic, generalized cubic, logarithmic, exponential, polynomial, spherical and others. And different image post-processing algorithms like Wiener filter, SVD method, wavelet transform, minimum mean square error method and others are applied to achieve jointly-optimization. Although most of studies have shown excellent invariant of optical transfer function for imaging lens, but such invariance will be unsatisfied when manufacturing errors are considered. In this paper, we present a method to consider behavior of tolerance in computational imaging system from pure optical to optical - digital, which means lens and image post-processing are both included. An axial irradiance equalization phase coded imaging system is illustrated for tolerance sensitivity by using similarity of point spread function (PSF), Strehl ratio (SR), and root mean square error (RMSE) of restored images. Finally, we compare differences between presented method and Zemax.