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  2009, Vol. 22 Issue (4): 541-547    DOI:
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Regularized Possibilistic Linear Models Based Adaptive Filter for Image Restoration
GE Hong-Wei, WANG Shi-Tong
School of Information Technology, Jiangnan University, Wuxi 214122

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Abstract  Median filter is widely used to remove impulsive noise but it distorts the fine structure of signals. To improve the median filter, an adaptive filter controlled by regularized possibilistic linear models is proposed. The proposed filter achieves good results through a summation of the input signal and the output of median filter. The weights are set based on regularized possibilistic linear models according to the states of the input signal sequence. The experimental results of image denoising show this filter effectively suppresses impulsive noises and simultaneously preserves image details. Moreover, the proposed filter has excellent robustness to various percentages of impulse noise in the testing examples.
Key wordsImpulse Noise      Regularized Possibilistic Linear Model      Median Filter      Image Restoration     
Received: 28 July 2008     
ZTFLH: TP391  
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GE Hong-Wei
WANG Shi-Tong
Cite this article:   
GE Hong-Wei,WANG Shi-Tong. Regularized Possibilistic Linear Models Based Adaptive Filter for Image Restoration[J]. , 2009, 22(4): 541-547.
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http://manu46.magtech.com.cn/Jweb_prai/EN/      OR     http://manu46.magtech.com.cn/Jweb_prai/EN/Y2009/V22/I4/541
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