Super-Resolution (SR) is a technique that has been exhaustively exploited and incorporates strategic aspects to image processing. As quantum computers gradually evolve and provide unconditional proof of computational advantage at solving intractable problems over their classical counterparts, quantum computing emerges with the compelling prospect to offer exponential speedup to process computationally expensive operations, such as the ones verified in SR imaging. Envisioning the design of a quantum-ready method for near-term noisy devices and igniting Rapid and Accurate Image Super Resolution (RAISR), an implementation using Variational Quantum Eigensolver (VQE) is demonstrated. This study proposes an approach that combines the benefits of RAISR, a non hallucinating and computationally efficient method, and VQE, a hybrid classical-quantum algorithm, to conduct SR with the support of quantum computation, preserving quantitative performance in terms of Image Quality Assessment (IQA).
Paper Details
- Authors:
- Submitted On:
- 14 November 2019 - 4:13pm
- Short Link:
- Type:
- Presentation Slides
- Event:
- Presenter's Name:
- Ystallonne C. S. Alves
- Paper Code:
- 1570564488
- Document Year:
- 2019
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Keywords
- Image/Video Processing
- Other applications of machine learning (MLR-APPL)
- Multimedia computing systems and applications
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url = {http://sigport.org/4956},
author = { },
publisher = {IEEE SigPort},
title = {Super-Resolution for Imagery Enhancement Using Variational Quantum Eigensolver},
year = {2019} }
T1 - Super-Resolution for Imagery Enhancement Using Variational Quantum Eigensolver
AU -
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4956
ER -