Depth map estimation using focus and aperture bracketing from a modified Canon 600D camera
Year: 2017
Type: dissertation
Abstract: In this work, we propose a variational model for depth estimation from an image sequence of a combined focus and aperture bracketing. In order to acquire the bracketed images, we modified a Canon 600D DSLR camera. We model the depth estimation problem as a minimization of an energy functional with a data fidelity term that takes into account the focus measures from different apertures. The energy to minimize is completed with a regularization term based on the Total Variation. Depth estimation using focus measures relies on local contrast. Homogeneous regions of the image have low local contrast, independently if they are focused or not, so this affects to the rightness of the estimated depth map. To overcome this problem, we propose a measure of reliability of the depth map and use inpainting techniques to improve the depth values on those areas with low reliability. The work is completed with the computation of an all-in-focus image. Finally, we also show experiments over different focus/aperture bracketings from various scenes and evaluate the behaviour of the algorithm by contrasting certain parameters.
Author: Àlex Palomo Domínguez
Language: English
Subfield: Media Technology
Field: Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W2761867811