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一种量子图像的中值滤波方案

赵娅 郭嘉慧 李盼池

赵娅, 郭嘉慧, 李盼池. 一种量子图像的中值滤波方案[J]. 电子与信息学报, 2021, 43(1): 204-211. doi: 10.11999/JEIT191038
引用本文: 赵娅, 郭嘉慧, 李盼池. 一种量子图像的中值滤波方案[J]. 电子与信息学报, 2021, 43(1): 204-211. doi: 10.11999/JEIT191038
Ya ZHAO, Jiahui GUO, Panchi LI. A Median Filtering Scheme for Quantum Images[J]. Journal of Electronics & Information Technology, 2021, 43(1): 204-211. doi: 10.11999/JEIT191038
Citation: Ya ZHAO, Jiahui GUO, Panchi LI. A Median Filtering Scheme for Quantum Images[J]. Journal of Electronics & Information Technology, 2021, 43(1): 204-211. doi: 10.11999/JEIT191038

一种量子图像的中值滤波方案

doi: 10.11999/JEIT191038
基金项目: 国家自然科学基金(61702093),东北石油大学青年科学基金(2020QNL-08)
详细信息
    作者简介:

    赵娅:女,1980年生,副教授,研究方向为量子衍生计算和量子图像处理

    郭嘉慧:女,1995年生,硕士生,研究方向为量子图像处理

    李盼池:男,1969年生,教授,研究方向为量子衍生计算和量子图像处理

    通讯作者:

    李盼池 lipanchi@vip.sina.com

  • 中图分类号: TP391

A Median Filtering Scheme for Quantum Images

Funds: The National Natural Science Foundation of China (61702093), The Youth Science Foundation of Northeast Petroleum University (2020QNL-08)
  • 摘要:

    中值滤波是经典图像处理中的基本滤波方法,然而在量子图像处理中相关模型尚不多见。为解决量子图像的中值滤波问题,该文提出了基于量子中值计算的新方法。该方法采用迭代比较的方法将目标像素排序,进而得到中值。文中首先介绍了实现中值滤波所需的各种基本模块的量子线路,然后重点介绍了中值计算的量子实现方法,最后给出了量子图像中值滤波的总体线路框架。复杂度分析表明该方法具有对经典算法的指数加速。经典计算机上的仿真结果验证了提出方法的有效性及可行性。

  • 图  1  一幅2×2的灰度图像

    图  2  量子比较器线路

    图  3  量子模加法器线路

    图  4  复制模块的量子线路

    图  5  复制模块的量子线路

    图  6  C2, C3, C9模块的量子线路

    图  7  中值计算模块的量子线路

    图  8  中值计算模块的量子线路

    图  9  仿真中用到的5幅灰度图像

    图  10  不同概率阈值下的量子比特翻转噪声图像

    图  11  不同概率阈值下量子噪声图像的滤波效果

    表  1  循环比较算法

     循环比较算法的具体实现
     循环($i = 2\;\;{\rm{to}}\;\;9$)
       如果$i < 9$,则$k = i - 1$,否则$k = i - 4$
       循环($j = 1\;\;{\rm{to}}\;\;k$)
         比较${c_j},{c_i}$,若${c_j} < {c_i}$,则交换${c_j},{c_i}$
    下载: 导出CSV

    表  2  两种方案滤波前后的峰值信噪比对比(dB)

    图像椒盐噪声高斯噪声泊松噪声
    滤波前经典方案本文方案滤波前经典方案本文方案滤波前经典方案本文方案
    (a)14.4532.2817.8334.3519.9018.4828.9510.4729.2710.7927.6635.507.8435.637.97
    (b)14.7332.7217.9934.8720.1418.0828.9110.8329.1911.1127.2335.748.5135.848.61
    (c)14.7530.8616.1132.3017.5517.9128.5110.6028.7810.8725.8733.427.5533.527.65
    (d)14.8330.6915.8631.9317.1017.8028.0710.2728.3410.5425.6232.707.0832.807.18
    (e)14.6831.5516.8733.2018.5217.9728.6610.6928.9510.9826.6834.557.8734.677.99
    平均14.6931.6216.9333.3318.6418.0528.6210.5728.9110.8626.6134.387.7734.497.88
    下载: 导出CSV

    表  3  量子噪声图像滤波前后的峰值信噪比对比(dB)

    图像概率阈值0.05概率阈值0.06概率阈值0.08概率阈值0.10
    滤波前滤波后滤波前滤波后滤波前滤波后滤波前滤波后
    (a)18.8936.0717.1818.1435.3617.2217.0733.9016.8316.1932.2716.08
    (b)18.8836.3617.4818.1535.8817.7317.0334.4217.3916.1633.0016.84
    (c)18.6333.2914.6617.9633.0315.0716.9132.3615.4516.0731.4215.35
    (d)18.6433.7015.0617.9832.4114.4316.9131.7814.8716.0730.8014.73
    (e)18.7935.5216.7318.1034.2416.1416.9333.1916.2616.0931.9915.9
    平均18.7734.9916.2218.0734.1816.1216.9733.1316.1616.1231.9015.78
    下载: 导出CSV
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出版历程
  • 收稿日期:  2019-12-25
  • 修回日期:  2020-07-08
  • 网络出版日期:  2020-07-22
  • 刊出日期:  2021-01-15

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