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Spatial and Angular Resolution Enhancement of Light Fields Using Convolutional Neural Networks.

Authors
  • Gul, M Shahzeb Khan
  • Gunturk, Bahadir K
Type
Published Article
Journal
IEEE Transactions on Image Processing
Publisher
Institute of Electrical and Electronics Engineers
Publication Date
May 01, 2018
Volume
27
Issue
5
Pages
2146–2159
Identifiers
DOI: 10.1109/TIP.2018.2794181
PMID: 29432097
Source
Medline
License
Unknown

Abstract

Light field imaging extends the traditional photography by capturing both spatial and angular distribution of light, which enables new capabilities, including post-capture refocusing, post-capture aperture control, and depth estimation from a single shot. Micro-lens array (MLA) based light field cameras offer a cost-effective approach to capture light field. A major drawback of MLA based light field cameras is low spatial resolution, which is due to the fact that a single image sensor is shared to capture both spatial and angular information. In this paper, we present a learning based light field enhancement approach. Both spatial and angular resolution of captured light field is enhanced using convolutional neural networks. The proposed method is tested with real light field data captured with a Lytro light field camera, clearly demonstrating spatial and angular resolution improvement.

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