# Hybrid Light Field Imaging for Improved Spatial Resolution and Depth Range

arXiv: https://arxiv.org/abs/1611.05008 · HTML: https://mlsanity.com/paper/1611.05008/

## Key facts

- Cited by 6 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 15 Nov 2016.

## Built on by (most cited first, 6 of 6)

- [Learning Texture Transformer Network for Light Field Super-Resolution](https://mlsanity.com/paper/2210.09293/) (2022)
- [Trade-off Between Spatial and Angular Resolution in Facial Recognition](https://mlsanity.com/paper/2402.07263/) (2024)
- [Depth-Aware Image and Video Orientation Estimation](https://mlsanity.com/paper/2604.13995/) (2026)
- [Self-supervised Learning-based Reconstruction of High-resolution 4D Light Fields](https://mlsanity.com/paper/2402.19020/) (2024)
- [Light Field Spatial Resolution Enhancement Framework](https://mlsanity.com/paper/2405.02787/) (2024)
- [Jointly Learning Spatial, Angular, and Temporal Information for Enhanced Lane Detection](https://mlsanity.com/paper/2405.02792/) (2024)

## Abstract (arXiv)

Light field imaging involves capturing both angular and spatial distribution of light; it enables new capabilities, such as post-capture digital refocusing, camera aperture adjustment, perspective shift, and depth estimation. Micro-lens array (MLA) based light field cameras provide a cost-effective approach to light field imaging. There are two main limitations of MLA-based light field cameras: low spatial resolution and narrow baseline. While low spatial resolution limits the general purpose use and applicability of light field cameras, narrow baseline limits the depth estimation range and accuracy. In this paper, we present a hybrid stereo imaging system that includes a light field camera and a regular camera. The hybrid system addresses both spatial resolution and narrow baseline issues of the MLA-based light field cameras while preserving light field imaging capabilities.