为了在去除高斯噪声的同时更有效地保持图像的边缘和细节,提出了信噪局部方差自适应的小波滤波方法.根据图像与高斯噪声的小波系数的分布特征,提出了一种信噪局部方差自适应的阈值.同时,鉴于无噪图像的小波系数具有平滑连贯性,提出一种...为了在去除高斯噪声的同时更有效地保持图像的边缘和细节,提出了信噪局部方差自适应的小波滤波方法.根据图像与高斯噪声的小波系数的分布特征,提出了一种信噪局部方差自适应的阈值.同时,鉴于无噪图像的小波系数具有平滑连贯性,提出一种连续的、可微的且无限逼近原小波系数的阈值函数.阈值依据信噪强度对信号系数与噪声系数进行区分,阈值函数依据阈值对小波系数进行量化处理,以去除噪声.实验结果表明,所提出的方法对图像去噪所得的PSNR(peak signal to noise ratio)和SSIM(structural similarity index)值以及图像的视觉效果,相对于现有的小波去噪方法有较大的提升,在彻底去除高斯噪声同时,更有效地保持图像的边缘和细节.展开更多
Enhanced speech based on the traditional wavelet threshold function had auditory oscillation distortion and the low signal-to-noise ratio (SNR). In order to solve these problems, a new continuous differentiable thresh...Enhanced speech based on the traditional wavelet threshold function had auditory oscillation distortion and the low signal-to-noise ratio (SNR). In order to solve these problems, a new continuous differentiable threshold function for speech enhancement was presented. Firstly, the function adopted narrow threshold areas, preserved the smaller signal speech, and improved the speech quality; secondly, based on the properties of the continuous differentiable and non-fixed deviation, each area function was attained gradually by using the method of mathematical derivation. It ensured that enhanced speech was continuous and smooth; it removed the auditory oscillation distortion; finally, combined with the Bark wavelet packets, it further improved human auditory perception. Experimental results show that the segmental SNR and PESQ (perceptual evaluation of speech quality) of the enhanced speech using this method increase effectively, compared with the existing speech enhancement algorithms based on wavelet threshold.展开更多
文摘为了在去除高斯噪声的同时更有效地保持图像的边缘和细节,提出了信噪局部方差自适应的小波滤波方法.根据图像与高斯噪声的小波系数的分布特征,提出了一种信噪局部方差自适应的阈值.同时,鉴于无噪图像的小波系数具有平滑连贯性,提出一种连续的、可微的且无限逼近原小波系数的阈值函数.阈值依据信噪强度对信号系数与噪声系数进行区分,阈值函数依据阈值对小波系数进行量化处理,以去除噪声.实验结果表明,所提出的方法对图像去噪所得的PSNR(peak signal to noise ratio)和SSIM(structural similarity index)值以及图像的视觉效果,相对于现有的小波去噪方法有较大的提升,在彻底去除高斯噪声同时,更有效地保持图像的边缘和细节.
基金Project(61072087) supported by the National Natural Science Foundation of ChinaProject(2011-035) supported by Shanxi Province Scholarship Foundation, China+2 种基金Project(20120010) supported by Universities High-tech Foundation Projects, ChinaProject (2013021016-1) supported by the Youth Science and Technology Foundation of Shanxi Province, ChinaProjects(2013011016-1, 2012011014-1) supported by the Natural Science Foundation of Shanxi Province, China
文摘Enhanced speech based on the traditional wavelet threshold function had auditory oscillation distortion and the low signal-to-noise ratio (SNR). In order to solve these problems, a new continuous differentiable threshold function for speech enhancement was presented. Firstly, the function adopted narrow threshold areas, preserved the smaller signal speech, and improved the speech quality; secondly, based on the properties of the continuous differentiable and non-fixed deviation, each area function was attained gradually by using the method of mathematical derivation. It ensured that enhanced speech was continuous and smooth; it removed the auditory oscillation distortion; finally, combined with the Bark wavelet packets, it further improved human auditory perception. Experimental results show that the segmental SNR and PESQ (perceptual evaluation of speech quality) of the enhanced speech using this method increase effectively, compared with the existing speech enhancement algorithms based on wavelet threshold.
