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  • 标题:Improved Gradients & Global Mean Based Switching Median Filter
  • 本地全文:下载
  • 作者:Lovepreet Kaur ; Dr. Arun Khosla
  • 期刊名称:International Journal of Engineering and Computer Science
  • 印刷版ISSN:2319-7242
  • 出版年度:2014
  • 卷号:3
  • 期号:7
  • 页码:6972-6977
  • 出版社:IJECS
  • 摘要:Noise in images has become one of the significant concerns in digital image processing. Many digital image basedtechniques produce inaccurate results when noise is presented in the digital images. So much researchers has proposednew and modified techniques so far to reduce or remove noise from images. Different kind of enhancement in the filtershas been proposed so far. But most of filters put artefacts while doing their work. Many filters fails when noise density inthe images is very high. Some filters results in over smoothed image i.e. poor for edges. This paper has proposed a newimproved global mean based switching median filter which has the capability to decrease the high density of the noisefrom images and also outperforms over others when input image is noise free. The proposed method has also ability topreserves the edges by using the gradient based smoothing. The proposed technique has been designed and implemented inMATLAB tool using image processing toolbox. Different kind of the digital images has been taken for experimentalpurpose. Comparative analysis has shown that the proposed algorithm is quite effective over the available techniques.
  • 关键词:Salt and pepper noise; Median filter; Smoothing and;Sharpening
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