【摘要】 阈值的选取和小波函数的构造是小波阈值去噪的关键,但传统的阈值去噪方法并没有对此进行充分的研究。针对传统小波阈值去噪分析的不足,分别从2个方面进行改进。首先,根据小波系数在各尺度上的相关性,提出了基于Lip指数阈值寻优的新方法;其次,用构造出新的小波阈值函数处理小波系数,克服了软阈值的高阶不可导和硬阈值函数的不连续,且计算方便。最后,对带有节子裂缝的木材图像进行去噪处理。实例验证了改进小波阈值法的优越性和有效性。更多还原

【Abstract】 Threshold selection and wavelet function construction were two key points of wavelet threshold denoising,which were not researched adequately in traditional threshold denoising methods. Deficiencies of traditional wavelet threshold methods in denoising were improved in two aspects. Firstly, according to the correlations of wavelet coefficients in different scales, new method for searching optimal threshold were proposed based on Lip exponent; secondly,new wavelet function was constructed to deal with wavelet coefficients, which not only convenient in calculating but also could overcome the non-differentiability in higher order of soft threshold and discontinuity of hard thresholding function; lastly, denoising treatment was done to the images of wood with knots and cracks. The superiority and effectiveness of improved wavelet thresholding method were tested.更多还原