量子电子学报 ›› 2025, Vol. 42 ›› Issue (1): 56-0.doi: 10.3969/j.issn.1007-5461.2025.01.006

• 图像与信息处理 • 上一篇    下一篇

任意大小二值图像的量子描述及形态学处理方法

张亚奇 , 赵 娅 , 李盼池 *   

  1. 东北石油大学计算机与信息技术学院, 黑龙江 大庆 163318
  • 收稿日期:2023-04-03 修回日期:2023-07-10 出版日期:2025-01-28 发布日期:2025-01-28
  • 通讯作者: E-mail: lipanchi@vip.sina.com E-mail:E-mail: lipanchi@vip.sina.com
  • 作者简介:张亚奇 ( 1998 - ), 女, 山东济宁人, 研究生, 主要从事量子图像处理方面的研究。E-mail: 2059735983@qq.com
  • 基金资助:
    黑龙江省自然科学基金 (LH2022F006)

Quantum representation and morphological processing of binary image with arbitrary size

ZHANG Yaqi, ZHAO Ya, LI Panchi *   

  1. School of Computer and Information Technology, Northeast Petroleum University, Daqing 163318, China
  • Received:2023-04-03 Revised:2023-07-10 Published:2025-01-28 Online:2025-01-28

摘要: 为解决量子计算机上图像的形态学处理问题, 研究了几种量子图像的形态学处理方法。首先, 提出了一种 改进的任意大小图像的量子描述方法, 该方法对于像素值和像素位置均采用量子基态描述, 其中描述像素位置的量 子基态数量等于像素个数。随后, 通过设计“ 膨胀、腐蚀” 这两种基本操作的量子线路, 设计出几种二值图像的量子 形态学处理方法, 包括: 图像去噪、边界提取、骨架提取。最后, 通过经典计算机上的仿真, 验证了所设计的几种量子 形态学方法的执行效果, 并基于所用基本量子门数量分析了量子线路的复杂度。研究结果表明, 本工作提出的方法 可以实现对经典方法的加速。

关键词: 图像处理, 量子形态学处理, 量子图像表示, 量子形态学膨胀, 量子形态学腐蚀

Abstract: To address the morphological processing problem of images on quantum computers, several morphological processing methods for quantum images were studied. Firstly, an improved quantum representation method for images with any size was proposed. In the method, both pixel value and pixel position were represented by quantum basis state, and the number of quantum basis states representing pixel positions was equal to the number of pixels. Then, by designing quantum circuits for the two basic operations of dilation and erosion, several quantum morphological processing methods for binary images were designed, including noise removal, boundary extraction, and skeleton extraction. Finally, the implementation effect of the designed methods was verified through simulation on classical computer, and the complexity of quantum circuits was analyzed based on the number of basic quantum gates used. The results show that the methods proposed in this work can achieve speedup over classical methods.

Key words: image processing, quantum morphological processing, quantum image representation, quantum morphological dilation, quantum morphological erosion

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