摘要： 传统图像去噪方法存在失真问题，造成失真的主要原因有：(1)在去噪的过程中把噪声点的影响分散到其邻域内；(2)对相应点没有判别其是否是噪声点；(3)判别噪声点不准确，将非噪声点误判为噪声点。针对这3个主因给出相应优化方案，通过生成测量算子及噪声可信度确定噪声点及其邻域内的噪声点。仿真实验结果证明，与中值滤波方法相比，该方法具有更强的去噪能力，能够达到防失真的目的。

关键词: 量子测量算子, 噪声点可信度, 噪声区域可信度, 争议噪声区域

Abstract: The traditional methods of image de-noising may bring distortion with many reasons. For the following reasons, this paper puts forward corresponding optimization program. The reason can be described as follows: in the process of de-noising, scattered the impact of the noise points into their neighborhood, it does not do judge some points whether they are noise points or not, it can not accurately judge whether a point is a noise point, the non-noise point might be wrongly judged as a noise point. This paper finds noise points and their neighborhood through the generation of noise points and noise measurement operator reliability. Simulation experimental result shows the method has stronger de-noising capability than the median filter method and can achieve the anti-distortion effect.

Key words: quantum measurement operator, noise point reliability, noise regional reliability, noise dispute area

中图分类号: 

• TP311