We introduce a novel and uniform framework for quantum pixel representations that overarches many of the most popular representations proposed in the recent literature, such as (I)FRQI, (I)NEQR, MCRQI, and (I)NCQI. The proposed QPIXL framework results in more efficient circuit implementations and significantly reduces the gate complexity for all considered quantum pixel representations. Our method only requires a linear number of gates in terms of the number of pixels and does not use ancilla qubits. Furthermore, the circuits only consist of Ry gates and CNOT gates making them practical in the NISQ era. Additionally, we propose a circuit and image compression algorithm that is shown to be highly effective, being able to reduce the necessary gates to prepare an FRQI state for example scientific images by up to 90% without sacrificing image quality. Our algorithms are made publicly available as part of QPIXL++, a Quantum Image Pixel Library.

翻译：对于量子像素表示,我们引入了一个新颖和统一的量子像素表示结构框架,它高估了最近文献中提议的许多最受欢迎的表示方式,如(I)FRQI、(I)NEQR、MCRQI和(I)NCQI。 拟议的QPIXL框架导致更高效的电路实施,并大大降低了所有被考虑的量子像素表示方式的门复杂性。我们的方法只要求用像素数量来表示直线数的门,而没有使用 ⁇ 。此外,电路只包括Ry门和CNOT门,使它们在新谢克尔时代变得实用。此外,我们提出了一种显示非常有效的电路和图像压缩算法,能够减少必要的门来准备一种FRIQI状态,例如科学图像的门高达90%,而不牺牲图像质量。我们的算法作为QPIXL+(一个量子图象像像像像像像像图书馆)的一部分公开提供。