北京航空航天大学学报 ›› 2013, Vol. 39 ›› Issue (11): 1443-1448.

• 论文 • 上一篇    下一篇

基于双量子比特态测量的量子自适应中值滤波

袁素真, 毛峡, 陈立江, 薛雨丽   

  1. 北京航空航天大学 电子信息工程学院, 北京 100191
  • 收稿日期:2013-01-28 出版日期:2013-11-30 发布日期:2013-12-04
  • 基金资助:
    国家自然科学基金资助项目(61103097);高等学校博士学科点专项科研基金资助项目(20121102130001)

Quantum adaptive median filtering based on dual qubits state measurement

Yuan Suzhen, Mao Xia, Chen Lijang, Xue Yuli   

  1. School of Electronic and Information Engineering, Beijing University of Aeronautics and Astronautics, Beijing 100191, China
  • Received:2013-01-28 Online:2013-11-30 Published:2013-12-04

摘要: 为了进一步增强去噪时对图像细节的保护能力,并同时提高算法实时性,提出了基于双量子比特态测量的量子自适应中值滤波算法,该算法首先将待处理图像像素转化为量子叠加态,然后依据量子测量原理对此叠加态进行量子测量,最后将测量后的坍缩态转化为输出图像.该算法使用双量子比特态来描述单像素,拓展了单量子比特态与单像素的对应关系.双量子比特态的4个叠加基态增加了被描述像素的信息量,可以更精确地对像素进行操作.该算法根据噪声特点设计双量子比特态的概率密度公式,并根据测量坍缩态自适应地调整滤波窗口尺寸.实验证明,该算法与标准中值滤波和经典自适应中值滤波相比,具有更好的综合滤波能力,既可以有效地滤除噪声点,很好地保护图像细节,又具有很好的实时性.

Abstract: To further enhance the image detail protection ability, improve the algorithm real-time in the de-noising process, a quantum adaptive median filtering algorithm based on dual qubits state measurement was proposed. The algorithm firstly transformed the image pixel to quantum superposition state form; secondly, the quantum superposition state was measured based on quantum measurement theory; finally, output image was designed based on the measurement collapsing state. Expanding the traditional correspondence relationship between single pixel and single qubit state, the algorithm used dual qubits state to represent a single pixel. Dual qubits state has four superposition states so that it contains more information on the represented pixels and processes these pixels more accurately. Probability density of the dual qubits state was designed based on the noise characteristics, and the collapse states will adaptively increase the filtering window's size. Experiments show that the quantum adaptive median filtering algorithm has a better integrated filtering capability compared with median filtering and classical adaptive median filtering. The algorithm can remove the noise effectively, protect the detail well and has good real-time.

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