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图像去噪的组合优化滤波算法

An optimized compounding filtering algorithm for denoising in image
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摘要 小波变换具有良好的局部化分析特性和多分辨率分析特性,小波阈值法能很好的消除高斯白噪声,但对脉冲噪声无法消除。中值滤波对脉冲噪声能很好滤除,并具有良好的边缘保持特性。为了能很好消除图像中的混合噪声,文章提出了基于小波阈值法和门限递归中值滤波组合优化的图像去噪算法,仿真结果表明,该算法在去除图像中的混合噪声时,比其他传统去噪方法具有极大的优越性。 Wavelets transform has advantages of local analysis and multl-resolution analysis.Threshold-method of wavelet is good at eliminating gauss-noise,but cannot eliminate pulse-noise in image. Median filter has good abilities of eliminating pulse-noise and keeping edgo.In order to denoise in image,this paper puts forward an optimized denoising image algorithm based on threshold-method of wavelet and threshold-recursive median filter. Simulation results are given to demonstrate that the optimized compounding algorithm is more advantaged than other traditional methods in denoising image.
机构地区 湘南学院
出处 《长沙通信职业技术学院学报》 2009年第2期41-43,共3页 Journal of Changsha Telecommunications and Technology Vocational College
基金 湖南省教育厅科学研究资助项目(07c720)
关键词 小波阈值 门限递归中值滤波 图像消噪 threshold-method wavelet threshold-recursive median filter image denoising
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