Spectral Analysis With a Piecewise Separation Occlusion Model for Image-Based Rendering

Abstract

Occlusion is ubiquitous in the real world, and neglecting it will certainly lead to quality degeneration in a reconstructed light field (LF). In this paper, we derive a piecewise separation occlusion model (PSOM) for LF reconstruction that is optimized for occlusion in the continuous Fourier and integral domains. The PSOM is first obtained by determining the definite integral intervals between the occlusion and nonocclusion boundaries in the spatial domain along the camera direction. We then use these definite integral intervals to perform spectral analysis of the plenoptic function (POF) to derive the occluded and nonoccluded plenoptic spectra. Finally, we show that using the two sampling rates derived from the occluded and nonoccluded spectra is more effective than using a uniform sampling rate for reconstructing a single scene unless the scene is free of occlusion. Through numerical experiments on simulated signals and real-world inward-looking and outward-looking scenes, we demonstrate the effectiveness of our proposed approach.