Quantum image representation
We analysed the following image representation ways:
- qubit lattice [2];
- real ket [3];
- flexible representation of quantum images - FRQI [4];
- multi-channel Representation for Images - MCRQI [5];
- novel enhanced quantum representation of digital images - NEQR [6];
- novel quantum representation for log-polar images - QUALPI [7];
- quantum states for M colors and quantum states for N coordinates - QSMC and QSNC [8];
- a simple quantum representation - SQR [9];
- normal arbitrary quantum superposition state - NAQSS [10];
- generalized quantum image representation - GQIR [11];
- quantum representation of multi wavelength images - QRMW [12];
- quantum image representation based on bitplanes - BRQI [13];
- order-encoded quantum image model - OQIM [14];
- quantum representation of indexed images and its applications - QIIR [15];
- fourier transform qubit representation FTQR [16]; The underlined representations are already implemented in the current repo.
Implementations also include some of the image processing procedures which are discribed here.
Some attention to the Classical-to-quantum and Quantum-to-classical interfaces (C2QI and Q2CI) and testing with it the reliability of the quantum representation methods.
Classification
Metrics
- number of primitives (or big O notation);
- number of utilized qubits;
- circuit depth - read more;
- Quantum Volume - read more.
metric results of the gray-scaled images encoding:
Depth | Utilized qubits # | Quantum Volume |
---|---|---|
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Authors
Marina Lisnichenko - m.lisnichenko@innopolis.university;
Stanislav Protasov - s.protasov@innopolis.ru.
Related publication
One day paper link will be here