Self-Supervised Spatially Variant PSF Estimation for Aberration-Aware Depth-from-Defocus

arXiv:2402.18175v1 Announce Type: new
Abstract: In this paper, we address the task of aberration-aware depth-from-defocus (DfD), which takes account of spatially variant point spread functions (PSFs) of a real camera. To effectively obtain the spatially variant PSFs of a real camera without requiring any ground-truth PSFs, we propose a novel self-supervised learning method that leverages the pair of real sharp and blurred images, which can be easily captured by changing the aperture setting of the camera. In our PSF estimation, …

abstract arxiv cs.cv eess.iv functions ground-truth novel paper psf self-supervised learning supervised learning truth type