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基于小波多阈值和子带增强的图像去噪; Image Denoising Based on Wavelet Multi-thresholding and Subband Enhancement
刘毅文 ; 李玲玲 ; 李翠华 ; 金泰松
2012
关键词小波变换 多阈值去噪 子带增强 混合阈值函数 wavelet transform multi thresholds denoising subband enhancement hybrid threshold function
英文摘要为了在有效降低噪声的同时,尽量保留图像的边缘特征,提出了一种基于小波多阈值和子带增强的图像去噪方法.该方法对最小尺度小波系数采取软阈值方式,将其他小波系数再分解为近似子带和细节子带,依据误差度增强近似子带像素块,同时引入增强因子调节增强幅度;利用局部方差和混合阈值函数对各子带进行阈值处理,保证了图像达到较好的去噪效果.实验表明,与传统阈值方法相比,该方法不仅提高了去噪图像的峰值信噪比,而且较好地保留图像边缘特征,优于常规的阈值方法.; To maintain more edge features in the process of reducing image-noise effectively.A wavelet multi-thresholding for image de-noise associating with subband enhancement was proposed.The soft threshold operator removes the wavelet coefficients on a minimum scale.The other wavelet coefficients are divided into approximate subbands and detail subbands,then the pixel blocks of approximate subbands can be enhanced based on the error value;at the same time,the enhanced amplitude is well regulated by adding the plus factor.The image denoising effect is great by using local variance and hybrid threshold function for those subbands.The experimental results show that the proposed denoising method can increase the peak signal noise to ratio(PSNR) and maintain as many as possible the important edge features.Thus it has better performance than commonly used threshold method.; 教育部新世纪优秀人才支持计划(NCET090126);河南省重点科技攻关项目(112102310082);国防基础科研计划项目(B1420110155);福建省自然科学基金项目(2011J01365)
语种zh_CN
内容类型期刊论文
源URL[http://dspace.xmu.edu.cn/handle/2288/102789]  
专题管理学院-已发表论文
推荐引用方式
GB/T 7714
刘毅文,李玲玲,李翠华,等. 基于小波多阈值和子带增强的图像去噪, Image Denoising Based on Wavelet Multi-thresholding and Subband Enhancement[J],2012.
APA 刘毅文,李玲玲,李翠华,&金泰松.(2012).基于小波多阈值和子带增强的图像去噪..
MLA 刘毅文,et al."基于小波多阈值和子带增强的图像去噪".(2012).
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