改进小波阈值法在木材图像缺陷处理中的应用  

Application of improved wavelet thresholding method in defect processing of timber image

作　　者：王旭[1] 李小舟 雷庆锋[1] 李艳杰[1] WANG Xu;LI Xiaozhou;LEI Qingfeng;LI Yanjie(Liaoning ForestryVocation Technical College, Shenyang 110101, China)

机构地区：[1]辽宁林业职业技术学院,辽宁沈阳110101

出　　处：《辽宁林业科技》2017年第5期18-21,33,共5页Liaoning Forestry Science and Technology

基　　金：基金项目 小波阈值去噪法在变形监测数据处理中的应用研究(KJ201505)

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。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 waveletthreshold methods in denoising were improved in two aspects.Firstly,according to the correlations of wavelet coefficientsin 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 alsocould 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 effectivenessof improved wavelet thresholding method were tested.

关 键 词：木材缺陷 小波去噪 阈值函数 图像处理 均方误差 

分 类 号：S781.5[农业科学—木材科学与技术]