第 32 卷摇 第 3 期 吉 林 大 学 学 报 (信 息 科 学 版) Vol. 32摇 No. 3
2014 年 5 月 Journal of Jilin University (Information Science Edition) May 2014
文章编号:1671鄄5896(2014)03鄄0239鄄08
基于改进 HWD 的小波阈值法图纸去噪研究
收稿日期: 2013鄄10鄄26
基金项目:国家自然基金资助项目(61374127); 黑龙江省教育厅科学技术研究基金资助项目(12511014); 黑龙江省博士后科研基金资
助项目(LBH鄄Q12143)
作者简介:任伟建(1963—摇 ), 女, 黑龙江泰来人, 东北石油大学教授, 博士生导师, 主要从事复杂系统的建模与控制研究, (Tel)86鄄
13845901386(E鄄mail)renwj@ 126. com。
任伟建
1
, 任摇 璐
1
, 公丽颖
2
, 石摇 阔
1
(1. 东北石油大学 电气信息工程学院, 黑龙江 大庆 163318; 2. 胜利油田胜利软件有限责任公司, 山东 东营 257000)
摘要: 针对小波阈值法中的小波变换只能将图像分解到有限方向, 而不能较好地表征图像多方向性的问题, 用
改进混合小波鄄方向滤波器组(HWD: Hybrid Wavelet鄄Directional filter banks) 变换代替单纯小波变换, 使在图像
分解过程中更好地表征图像的多方向性, 保存更多的图像信息; 在分析小波阈值去噪原理的基础上, 改变隶属
度函数, 构建 HWD 隶属度的权系数, 从而避免因小波系数间存在幅值交叉使小波阈值法的应用受到限制。 改
进的 HWD 在损失最少图像小波系数的前提下, 能最大限度地置零噪声小波系数。 实际工程图纸去噪研究表
明, 改进的小波阈值法可在去除一定噪声的前提下, 保留更多的工程图纸细节信息。
关键词: 小波变换; 方向滤波器; 小波阈值法; 工程图纸去噪
中图分类号: TP391 文献标识码: A
Research on Drawings Denoising Based on Improved Wavelet Threshold
Algorithm with Hybrid Wavelet鄄Directional Filter Transform
REN Weijian
1
, REN Lu
1
, GONG Liying
2
, SHI Kuo
1
(1. College of Electrical and Information Engineering, Northeast Petroleum University, Daqing 163318, China;
2. Shengli Oil Field Victorysoftware Company Limited, Dongying 257000, China)
Abstract: For the defects that the image can only be decomposed into a finite orientation by the wavelet
transformation, and multi鄄directional of image can not be better characterized, the directional filter is applied to
the method of wavelet threshold, namely, the HWD ( Hybrid Wavelet鄄Directional filter banks) instead of the
mere wavelet transform is used to better characterized the multi鄄directional of image and to retain more image
information. To avoid the phenomenon of amplitude cross exists between image wavelet coefficients and noise
wavelet coefficients, the method of wavelet thresholding was restricted by this shortcoming, membership function
was changed based on the principle of the wavelet, and the membership weights of HWD was built by the
membership function. The wavelet coefficients of noise were set to zero maximum with losing the image
coefficients at least by this improved HWD. The wavelet coefficients of noise were set to zero maximum with
losing the image coefficients at least by this improved HWD. The studies show that more details of engineering
drawings can be retained by the improved wavelet threshold method beside removing some noise.
Key words: wavelet transform; directional filter; wavelet thresholding algorithm; engineering drawings denoising
0摇 引摇 言
随着现代化工业的不断发展, 工程图纸数字化已成为当前发展趋势, 而数字化后的图纸图像在获取
或传输过程中不可避免地会受到噪声污染, 对其进行去噪处理也势必成为人们研究的热点。 人们在研究