论文标题
使用状态连接
Block-wise quantum grayscale image representation and compression scheme using state connection
论文作者
论文摘要
与经典计算相比，量子计算的计算能力更快，因此引起了巨大的关注，以表示和压缩经典图像数据到量子域中。量子域表示的主要思想是转换像素强度及其坐标，即使用量子位（即Qubits）进行状态标签制备。对于更大尺寸的图像，状态标签制备需要更多的量子。为了解决更多量子位问题，已经提出了一种新颖的SCMNEQR（状态连接修改新颖的增强量子表示）方法，该方法使用较少的量子位使用块智能状态标签制备来绘制灰度图像的任意大小。提出的SCMNEQR方法使用复位门引入状态连接，而不是重复使用现有方法中使用的Toffoli Gate。实验结果表明，所提出的方法在压缩方面优于现有方法。
Quantum computing draws huge attention due to its faster computational capability compared to classical computing to represent and compress the classical image data into the quantum domain. The main idea of quantum domain representation is to convert pixel intensities and their coordinates i.e. state label preparation using quantum bits i.e. Qubits. For a bigger size image, the state label preparation takes more Qubits. To address more Qubits issues, a novel SCMNEQR (State Connection Modification Novel Enhanced Quantum Representation) approach has been proposed that uses fewer qubits to map the arbitrary size of the grayscale image using block-wise state label preparation. The proposed SCMNEQR approach introduces the state connection using a reset gate rather than repeating the use of the Toffoli gate used in the existing approach. The experimental results show that the proposed approach outperforms the existing methods in terms of compression.
