计算机科学 ›› 2017, Vol. 44 ›› Issue (8): 301-305.doi: 10.11896/j.issn.1002-137X.2017.08.052

• 图形图像与模式识别 • 上一篇    下一篇

基于粒子群算法的图像椒盐噪声去除算法

张爱玲,李鹏,刘晟   

  1. 西安理工大学信息技术与装备工程学院 西安710082,西安电子科技大学电子工程学院 西安710068,西安理工大学信息技术与装备工程学院 西安710082
  • 出版日期:2018-11-13 发布日期:2018-11-13
  • 基金资助:
    本文受国家自然科学基金面上项目:地面三维激光扫描技术(TLS)在滑坡监测与评价中的应用研究(41372330),空军装备研究院第二研究所项目:干扰仿真系统(99901070034)资助

Algorithm of Image Salt and Pepper Noise Elimination Based on Particle Swarm Algorithm

ZHANG Ai-ling, LI Peng and LIU Sheng   

  • Online:2018-11-13 Published:2018-11-13

摘要: 针对图像中的椒盐噪声消除问题,提出了一种基于粒子群算法的自适应开关中值滤波算法。提出的滤波器算法主要由两大阶段组成:噪声检测阶段和噪声滤除阶段。与标准中值滤波相比,提出的自适应开关中值滤波算法能够生成污染图像的噪波图。通过噪波图可以得到图像的污染和未污染像素信息。在滤除过程中,滤波器计算出未污染相邻像素的中值并且替换污染像素。仿真实验结果证实了所提算法的有效性,其能够有效地提高图像的峰值信噪比和图像质量;相比现有其他方法,所提算法的去噪效果更好。

关键词: 中值滤波,粒子群算法,噪声消除,椒盐噪声,图像去噪,PSNR,NMSE

Abstract: To eliminate salt and pepper noise in images,we proposed an adaptive switching median filter algorithm based on particle swarm algorithm. The proposed algorithm consists of two stages:noise detection and noise filtering.Compared with the standard median filtering,the adaptive switching median filter algorithm was put forward to generate pollution image noise wave. Contaminated and non-contaminated pixel information can be get through the noise wave images.In the filtering process,the filter calculates the value of the adjacent pixels and replaces the contaminated pixels.The simulation results show that the proposed algorithm is effective and can improve the peak signal to noise ratio (SNR) and image quality.

Key words: Median filter,Particle swarm algorithm,Noise elimination,Impulse noise,Image denoising,PSNR,NMSE

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