论文标题
用于代表和压缩数字图像的量子计算的新型状态连接策略
A novel state connection strategy for quantum computing to represent and compress digital images
论文作者
论文摘要
与经典数据处理系统相比，由于更快的数据计算和存储，量子图像处理引起了很多关注。将经典图像数据转换为量子域和状态标签制备复杂性仍然是一个具有挑战性的问题。现有技术通常直接连接像素值和状态位置。最近，EFRQI（量子图像的有效柔性表示）方法使用辅助量子量子，该辅助量子将像素代表量子量线连接到通过Toffoli门的状态位置码头，以减少状态连接。由于每个像素连接的Toffoli门两次使用，因此需要大量的位才能连接每个像素值。在本文中，我们提出了一种新的SCMFRQI（状态连接修改FRQI）方法，用于通过使用重置门修改状态连接而不是重复使用相同的Toffoli Gate连接作为重置门来进一步降低所需位。此外，与其他现有方法不同，我们使用块级压缩图像，以进一步降低所需量子位。实验结果证实，根据图像表示和压缩的观点，所提出的方法优于现有方法。
Quantum image processing draws a lot of attention due to faster data computation and storage compared to classical data processing systems. Converting classical image data into the quantum domain and state label preparation complexity is still a challenging issue. The existing techniques normally connect the pixel values and the state position directly. Recently, the EFRQI (efficient flexible representation of the quantum image) approach uses an auxiliary qubit that connects the pixel-representing qubits to the state position qubits via Toffoli gates to reduce state connection. Due to the twice use of Toffoli gates for each pixel connection still it requires a significant number of bits to connect each pixel value. In this paper, we propose a new SCMFRQI (state connection modification FRQI) approach for further reducing the required bits by modifying the state connection using a reset gate rather than repeating the use of the same Toffoli gate connection as a reset gate. Moreover, unlike other existing methods, we compress images using block-level for further reduction of required qubits. The experimental results confirm that the proposed method outperforms the existing methods in terms of both image representation and compression points of view.
