Light Field Resolution Enhancement Framework

Light field (LF) imaging captures both angular and spatial light distributions, enabling advanced photographic techniques. However, micro-lens array (MLA)-based cameras face a spatial-angular resolution tradeoff due to a single shared sensor. We propose a novel light field framework f or resolution enhancement, employing a modular approach. The first module generates a high-resolution, all-in-focus image. The second module, a texture transformer network, enhances the resolution of each light field perspective independently u sing the output of the first module as a reference image. The final module leverages light field regularity to jointly improve resolution across all LF image perspectives. Our approach demonstrates superior performance to existing methods in both qualitative and quantitative evaluations.

Authors

Institutions

Publication Details

Published
2024-11-27
DOI
https://doi.org/10.1109/dicta63115.2024.00081
Primary Topic
Image Enhancement Techniques
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Light Field Resolution Enhancement Framework

Muhammad Zeshan Alam, M. Umair Mukati, Javeria Shabbir
Image Enhancement Techniques
article

Light Field Resolution Enhancement Framework

Muhammad Zeshan Alam, M. Umair Mukati, Javeria Shabbir
article en

Abstract

Light field (LF) imaging captures both angular and spatial light distributions, enabling advanced photographic techniques. However, micro-lens array (MLA)-based cameras face a spatial-angular resolution tradeoff due to a single shared sensor. We propose a novel light field framework f or resolution enhancement, employing a modular approach. The first module generates a high-resolution, all-in-focus image. The second module, a texture transformer network, enhances the resolution of each light field perspective independently u sing the output of the first module as a reference image. The final module leverages light field regularity to jointly improve resolution across all LF image perspectives. Our approach demonstrates superior performance to existing methods in both qualitative and quantitative evaluations.

Georgia Institute of Technology (US), Brandon University (CA), Technical University of Denmark (DK)
Openalex Percentile: Top 73%
Image Enhancement Techniques
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Light Field Resolution Enhancement Framework — Muhammad Zeshan Alam, M. Umair Mukati, et al. · (2024) | TGRS Research Map | TGRS