厦门大学学报（自然科学版）2012，Vol.51Issue(3)：342-347,6.
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
摘要
Abstract
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 mini mum 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.关键词
小波变换/多阈值去噪/子带增强/混合阈值函数Key words
wavelet transform/multi thresholds denoising/subband enhancement/hybrid threshold function分类
信息技术与安全科学引用本文复制引用
刘毅文,李玲玲,李翠华,金泰松..基于小波多阈值和子带增强的图像去噪[J].厦门大学学报（自然科学版）,2012,51(3):342-347,6.基金项目
教育部新世纪优秀人才支持计划(NCET090126) （NCET090126）
河南省重点科技攻关项目(112102310082) （112102310082）
国防基础科研计划项目(B1420110155) （B1420110155）
福建省自然科学基金项目(2011J01365) （2011J01365）
