To address the limitations of existing models that predominantly represent data in Cartesian coordinate systems and RGB color representations, this paper proposes YCrCbQPI (A Quantum Polar Coordinate Color Image Representation Model Based on YCrCb Color Space, YCrCb-QPI). This model integrates luminance and chrominance separation properties of YCrCb with the geometric invariance of logarithmic polar coordinates. Through a differentiated quantum encoding strategy, more qubits are allocated to critical luminance information while less sensitive chrominance information is assigned simplified encoding. Corresponding quantum state preparation circuits are also designed. Theoretical analysis indicates that compared to traditional RGB polar coordinate models, this model achieves significant savings in color information encoding resources while maintaining comparable visual fidelity. Furthermore, the model inherently possesses the rotation and scaling invariance of polar coordinates, establishing a robust foundation for developing efficient quantum image processing algorithms.
Mostly existing quantum image models represent image in Cartesian coor- dinates. Some complicated affine transformation can not be easily handled in Cartesian coordinates. In this paper, a new representation of Multi-Channel log-polar quantum im- age (MCLPQI) sampled in log-polar coordinates is proposed. This form contains the im- age RGB color information and transparency of the corresponding pixel. Then we give the polynomial preparation process which proves that our quantum image representation state can be made in a feasible time complexity. Finally we discussed color transfor- mation among different channels and single channel color transformations, transparency adjustments. Analysis demonstrates that the MCLPQI is a efficient quantum log-polar color image representation.
Quantum image representation has a significant impact in quantum image processing. In this paper, a bit-plane representation for log-polar quantum images (BRLQI) is proposed, which utilizes
(n+4) or
(n+6) qubits to store and process a grayscale or RGB color image of
2n pixels. Compared to a quantum log-polar image (QUALPI), the storage capacity of BRLQI improves 16 times. Moreover, several quantum operations based on BRLQI are proposed, including color information complement operation, bit-planes reversing operation, bit-planes translation operation and conditional exchange operations between bit-planes. Combining the above operations, we designed an image scrambling circuit suitable for the BRLQI model. Furthermore, comparison results of the scrambling circuits indicate that those operations based on BRLQI have a lower quantum cost than QUALPI. In addition, simulation experiments illustrate that the proposed scrambling algorithm is effective and efficient.