Light-field spectral decomposition with a spatial–angular consistency prior for disparity estimation

Abstract

Modeling the spatial–angular relationship is the theoretical basis for accurate disparity estimation from the light-field data. In this paper, the spatial–angular coupling relationship of light-field is established under the assumption of constant radiance along rays, and the spatial–angular consistency model of light-field is established under the assumption of Lambertian radiance. Based on the spatial–angular consistency prior of light-field, the light-field spectral decomposition based on disparity layers can be modeled as the ill-posed inverse problem. Based on the spectral decomposition, the disparity estimation is transformed into the process of searching for the spatial domain support set in the scene disparity hierarchy. The normalized cross-correlation function is utilized to estimate the disparity based on spectral decomposition under the spatial–angular consistency of the light-field. The performance on both simulated and real captured data show that the proposed algorithm is effective at high-precision and dense disparity estimation.