Open Quantum Computer Vision

A unified library for quantum image representation and processing, inspired by OpenCV but designed for quantum computing.

Overview

This library unifies various quantum image representation algorithms and provides quantum image processing operations. It combines the best of existing quantum image processing frameworks into a cohesive, easy-to-use package.

Key Features

• Unified API: Consistent interface across different quantum image representations
• Multiple Encodings: Support for both amplitude-encoded and computational basis-encoded schemes
• Quantum Processing: Built-in quantum image processing operations like denoising
• Comprehensive Metrics: Full suite of image quality assessment metrics
• Inspired by OpenCV: Familiar API design for classical computer vision users

Supported Representations

Amplitude Encoded

• QARQI: Quadrant Amplitude Representation of Quantum Images

  • Uses qudits for efficient encoding
  • Polarity-magnitude coordinate system
  • Controlled RY rotations for intensity encoding

• FRQI: Flexible Representation of Quantum Images

  • Position in basis states, intensity in amplitudes
  • Supports flexible quantum operations
  • Citation: Le et al. (2011)

Computational Basis Encoded

• MHRQI: Multi-scale Hierarchical Representation of Quantum Images

  • Hierarchical quantum circuits
  • Basis state encoding for intensities
  • Built-in denoising capabilities

• NEQR: Novel Enhanced Quantum Representation of digital images

  • Both position and intensity in basis states
  • Supports grayscale and color images
  • Citation: Zhang et al. (2013)

Installation

pip install open-quantum-computer-vision

Or from source:

git clone https://github.com/your-repo/open-quantum-computer-vision
cd open-quantum-computer-vision
pip install -e .

Quick Start

import numpy as np
from open_quantum_cv import MHRQI, QARQI

# Load an image
image = np.random.randint(0, 256, (16, 16), dtype=np.uint8)

# Use MHRQI (Computational Basis Encoding)
mhrqi = MHRQI(depth=4)
mhrqi.encode(image)
result = mhrqi.simulate(shots=1000)
reconstructed = result.reconstructed_image

# Use QARQI (Amplitude Encoding)
qarqi = QARQI(d=4)
qarqi.encode(image)
result = qarqi.simulate(shots=1000)
reconstructed = result.reconstructed_image

# Compute metrics
metrics = result.compute_metrics(image)
print(f"MSE: {metrics['mse']:.4f}, SSIM: {metrics['ssim']:.4f}")

Architecture

open_quantum_cv/
├── representations/     # Quantum image representations
│   ├── base.py         # Common interface
│   ├── mhrqi.py        # MHRQI implementation
│   └── qarqi.py        # QARQI implementation
├── processing/         # Quantum image processing
│   └── denoising.py    # Hierarchical denoising
├── utils/             # Utilities
│   ├── general.py     # Core utilities
│   ├── metrics.py     # Quality metrics
│   └── visualization.py # Plotting functions
├── benchmarks/        # Benchmarking tools
├── examples/          # Usage examples
└── tests/            # Unit tests

Dependencies

• Quantum Computing: Qiskit, Qiskit-Aer, MQT Qudits
• Image Processing: OpenCV, scikit-image
• Metrics: PIQ, PyPIQE, BRISQUE, scikit-video
• General: NumPy, SciPy, Matplotlib, PyTorch

Contributing

Contributions are welcome! Please see our contributing guidelines.

License

Apache 2.0

Citation

If you use this library in your research, please cite the original papers:

• MHRQI: Jose, K.S. et al. (2023). Multi-scale Hierarchical Representation of Quantum Images.
• QARQI: Jose, K.S. (2023). Quadrant Amplitude Representation of Quantum Images.
• FRQI: Le, P.Q., Dong, F. & Hirota, K. A flexible representation of quantum images for polynomial preparation, image compression, and processing operations. Quantum Inf Process 10, 63–84 (2011). https://doi.org/10.1007/s11128-010-0177-y
• NEQR: Zhang, Y., Lu, K., Gao, Y. et al. NEQR: a novel enhanced quantum representation of digital images. Quantum Inf Process 12, 2833–2860 (2013). https://doi.org/10.1007/s11128-013-0567-z

Acknowledgments

This library unifies and builds upon:

• MHRQI by Keno S. Jose
• QARQI by Keno S. Jose