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A Photonic System for Generating Unconditional Polarization-Entangled Photons Based on Multiple Quantum Interference
Published on: September 5, 2019
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Quantum realization of the bilinear interpolation method for NEQR
Ri-Gui Zhou1, Wenwen Hu2, Ping Fan3
1College of Information Engineering, Shanghai Maritime University, Shanghai, 201306, China.
Scientific Reports
|June 2, 2017
Summary
This study proves the feasibility of quantum bilinear interpolation for image scaling using novel enhanced quantum image representation (NEQR). Quantum scaling with bilinear interpolation yields clearer, less distorted images compared to nearest-neighbor methods.
Area of Science:
- Quantum computation and information science
- Quantum image processing and geometric transformations
Background:
- Quantum image processing is an emerging field within quantum computation.
- Image scaling is a fundamental classical image processing technique, but its quantum counterpart is underdeveloped.
Purpose of the Study:
- To investigate the feasibility of implementing classical bilinear interpolation within a quantum computing framework.
- To develop and analyze quantum circuits for image scaling using novel enhanced quantum image representation (NEQR).
Main Methods:
- Proving the theoretical feasibility of bilinear interpolation for NEQR.
- Designing concrete quantum circuits utilizing multi-controlled operations, adders, subtractors, multipliers, and division.
- Performing complexity analysis of the quantum circuits based on fundamental quantum gates.
Main Results:
- Demonstrated the feasibility of quantum bilinear interpolation for NEQR.
- Developed specific quantum circuits for both scaling up and scaling down NEQR images.
- Simulation results indicate superior image quality (clarity, reduced distortion) compared to nearest-neighbor interpolation.
Conclusions:
- Quantum bilinear interpolation is a viable method for image scaling in quantum image processing.
- The proposed quantum circuits offer a pathway for advanced quantum image geometric transformations.
- This work advances the development of quantum image processing capabilities, particularly for geometric transformations.
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