计算机与现代化 ›› 2023, Vol. 0 ›› Issue (04): 47-55.

• 图像处理 • 上一篇    下一篇

基于IBM Qiskit的量子图像伪彩色增强方法

  

  1. (北京石油化工学院信息工程学院,北京 102617)
  • 出版日期:2023-05-09 发布日期:2023-05-09
  • 作者简介:刘志飞(1996—),男,江苏南通人,硕士研究生,研究方向:量子图像处理,E-mail: 2019520129@bipt.edu.cn; 朱尚超(1995—),男,浙江杭州人,硕士研究生,研究方向:量子图像处理,E-mail: shangchaozhu@gmail.com; 通信作者:魏战红(1985—),女,山东临沂人,副教授,博士,研究方向:图像处理,量子信息隐藏及工业控制网络信息安全,E-mail: weizhanhong@bipt.edu.cn; 臧一鸣(1994—),女,河北保定人,硕士研究生,研究方向:量子图像处理,E-mail: zym520102@163.com; 孙文韬(1997—),男,山东德州人,硕士研究生,研究方向:量子图像处理,E-mail: 2020540249@bipt.edu.cn; 胡冠时(1990—),男,河北石家庄人,硕士研究生,研究方向:量子图像处理,E-mail: swiftninja@163.com。
  • 基金资助:
    国家自然科学基金青年科学基金资助项目(61702040); 北京市教委科研科技计划一般项目(KM201810017006); 北京市自然科学基金青年项目(4174089)

Pseudo-color Enhancement Method for Quantum Images Based on IBM Qiskit

  1. (School of Information Engineering, Beijing Institute of Petrochemical Technology, Beijing 102617, China)
  • Online:2023-05-09 Published:2023-05-09

摘要: 针对量子图像增强问题,提出一种基于彩虹编码的量子图像伪彩色增强方法。首先,使用NEQR (Novel Enhanced Quantum Representation)模型表示灰度图像,接着设计和优化RGB三通道颜色转换模块的量子线路,最后用QRMW (Quantum Representation of Multi Wavelength Images)模型表示伪彩色图像。为了验证所提方法的有效性,在IBM量子计算框架Qiskit上制备2×2大小与32×32大小的NEQR灰度图像,通过对量子线路测量坍缩后生成对应大小的QRMW伪彩色图像。实验结果表明,与经典和已有的量子图像伪彩色增强方法相比,该方法在处理大小为2n×2n、色深为2q的图像时,所需的量子基本门个数为958,时间复杂度仅为常数级O(1),空间复杂度为O(2n+2q+3),显著降低了量子成本,并且处理后图像的信息熵和清晰度指标良好。

关键词: 量子图像处理, 量子计算, 量子图像伪彩色增强, 彩虹编码

Abstract: Aiming at the problem of quantum image enhancement, a pseudo-color enhancement method for quantum images based on rainbow coding is proposed. Firstly, the NEQR (Novel Enhanced Quantum Representation) model is used to represent grayscale images, then the quantum circuit of the RGB three-channel color conversion module is designed and optimized, and finally the QRMW (Quantum Representation of Multi Wavelength Images) model is used to represent pseudo-color images. In order to verify the effectiveness of the proposed method, 2×2 and 32×32 NEQR grayscale images are prepared on the IBM quantum computing framework Qiskit, and QRMW pseudo-color images of corresponding sizes are generated by measuring the collapse of the quantum circuit. The experimental results show that, compared with the classical and existing quantum image pseudo-color enhancement methods, this method only requires 958 quantum fundamental gates when processing images with a size of 2n×2n and a color depth of 2q. The time complexity is constant-level O(1), and the space complexity is O(2n+2q+3), which significantly reduces the quantum cost, and the information entropy and sharpness indicators of the processed image are good.

Key words: quantum image processing, quantum computing, quantum image pseudo-color enhancement, rainbow coding