Light field reconstruction using shearlet transform in tensorflow
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review
Details
| Original language | English |
|---|---|
| Title of host publication | 2019 IEEE International Conference on Multimedia and Expo Workshops, ICMEW 2019 |
| Publisher | IEEE |
| ISBN (Electronic) | 9781538692141 |
| DOIs | |
| Publication status | Published - 1 Jul 2019 |
| Publication type | A4 Article in a conference publication |
| Event | IEEE International Conference on Multimedia and Expo Workshops - Shanghai, China Duration: 8 Jul 2019 → 12 Jul 2019 |
Conference
| Conference | IEEE International Conference on Multimedia and Expo Workshops |
|---|---|
| Country | China |
| City | Shanghai |
| Period | 8/07/19 → 12/07/19 |
Abstract
Shearlet Transform (ST) is one of the most effective approaches for light field reconstruction from Sparsely-Sampled Light Fields (SSLFs). This demo paper presents a comprehensive implementation of ST for light field reconstruction using one of the most popular machine learning libraries, i.e. Tensor Flow. The flexible architecture of TensorFlow allows for the easy deployment of ST across different platforms (CPUs, GPUs, TPUs) running varying operating systems with high efficiency and accuracy.
ASJC Scopus subject areas
Keywords
- Epipolar-Plane Image, Light Field Reconstruction, Light Field Sparsification, Shearlet Transform, TensorFlow
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Field of science, Statistics Finland
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