NGQR:一种新的广义量子图像表示

IF 5.4 2区 计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS
Zheng Xing;Xiaochen Yuan;Chan-Tong Lam;Penousal Machado
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引用次数: 0

摘要

为了解决现有量子图像模型在精确图像表示方面的尺寸限制,以及图像操作和检索的不准确性,我们提出了一种适用于任意大小和类型图像的新型广义量子图像表示(NGQR)。为了推广尺寸模型,我们首先提出了感知辅助编码(PE)方法来感知量子信息中的目标量子比特。在此基础上,我们提出了量子图像表示PE- ngqr,它可以精确地忽略冗余信息,从而针对有效像素进行操作和检索。然后,为了在没有冗余的情况下准确地表示所需的像素信息,我们提出了相干尺寸编码(Coherent-Size Encoding, CE)方法。CE可以编码任意数量的量子态。在此基础上,我们提出了一种能够精确表示、处理和检索图像的量子图像模型CE- ngqr。具体来说,我们详细描述了NGQR的概念、表示和量子电路。我们提供了详细的量子电路和基于ngqr的操作和几何变换的模拟。此外,NGQR实现了灵活的量子图像缩放。我们通过复杂性仿真说明了所提出的PE-NGQR和CE-NGQR的互补性,并阐明了各自的适用场景。最后,通过与现有量子图像模型的比较分析,证明了NGQR的通用性和灵活性优势。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
NGQR: A Novel Generalized Quantum Image Representation
To address the size limitations of existing quantum image models in terms of accurate image representation, as well as inaccurate image operation and retrieval, we propose a Novel Generalized Quantum Image Representation (NGQR) for images of arbitrary size and type. For generalizing the size model, we first propose the Perception-Aided Encoding (PE) method to perceive the target qubits in the quantum information. Based on PE, we propose the quantum image representation PE-NGQR, which accurately ignores redundant information thereby targeting valid pixels for operations and retrieval. Then, to accurately represent the needed pixel information without redundancy, we propose the Coherent-Size Encoding (CE) method. The CE can encode an arbitrary number of quantum states. Based on CE, we propose CE-NGQR, a quantum image model capable of accurate image representation, processing and retrieval. Specifically, we describe in detail the concept, representation and quantum circuits of NGQR. We provide detailed quantum circuits and simulations of NGQR-based operations and geometric transformations. Moreover, NGQR enables flexible quantum image scaling. We illustrate the complementarity of the proposed PE-NGQR and CE-NGQR through complexity simulations and clarify the respective applicability scenarios. Finally, comparisons and analyses with existing quantum image models demonstrate the versatility and flexibility advantages of NGQR.
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来源期刊
IEEE Transactions on Emerging Topics in Computing
IEEE Transactions on Emerging Topics in Computing Computer Science-Computer Science (miscellaneous)
CiteScore
12.10
自引率
5.10%
发文量
113
期刊介绍: IEEE Transactions on Emerging Topics in Computing publishes papers on emerging aspects of computer science, computing technology, and computing applications not currently covered by other IEEE Computer Society Transactions. Some examples of emerging topics in computing include: IT for Green, Synthetic and organic computing structures and systems, Advanced analytics, Social/occupational computing, Location-based/client computer systems, Morphic computer design, Electronic game systems, & Health-care IT.
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