[1]马坤,孙枭雄,多化琼*,等. 小波和傅里叶相融合的彩色木材图像增强[J].西北林学院学报,2019,34(3):196-201.[doi:10.3969/j.issn.1001-7461.2019.03.31]
　MA Kun,SUN Xiao-xiong,DUO Hua-qiong*,et al. Wavelet and Fourier Fusion of Color Wood Image Enhancement[J].JOURNAL OF NORTHWEST FORESTRY UNIVERSITY,2019,34(3):196-201.[doi:10.3969/j.issn.1001-7461.2019.03.31]
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 小波和傅里叶相融合的彩色木材图像增强()
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《西北林学院学报》[ISSN:1001-7461/CN:61-1202/S]

卷:
第34卷
期数:
2019年第3期
页码:
196-201
栏目:
出版日期:
2019-05-31

文章信息/Info

Title:
 Wavelet and Fourier Fusion of Color Wood Image Enhancement
文章编号:
1001-7461(2019)03-0196-06
作者:
 马坤1; 孙枭雄2; 多化琼1*; 汪宏1
 （1.内蒙古农业大学 材料科学与艺术设计学院，内蒙古 呼和浩特 010018；2.内蒙古民族大学 计算机科学与技术学院，内蒙古 通辽 028000）
Author(s):
 MA Kun1; SUN Xiao-xiong2; DUO Hua-qiong1*; WANG Hong1
 (1.College of Material Science and Art Design,Inner Mongolia Agriculuture University,Huhhot 010018,Inner Mongolia,China; 2.College of Computer Science and Technology,Inner Mongolia University for Nationnalities,Tongliao 028000,Inner Mongolia,China)
关键词:
 ; 彩色图像增强; 小波变换; 傅里叶变换; PSNR; 信息熵
Keywords:
 ; color image enhancement;  wavelet transform;  Fourier transform;  PSNR;  information entropy
分类号:
S781.1
DOI:
10.3969/j.issn.1001-7461.2019.03.31
文献标志码:
A
摘要:
 针对现实生活中彩色图像普遍存在不清晰和对比度差的情况，在RGB模型上提出了一种新的彩色图像增强算法，并且应用到了木材图像领域。将彩色木材图像分解为RGB 3个通道，首先使用滤波器把3个通道分别分解成高低频子带；然后使用傅立叶变换和小波变换相融合的方式进行锯齿检测，同时进行阈值判断；之后对检测到的锯齿进行消除，低频子带使用方向自适应滤波器，高频子带使用小波收缩函数进行消除；再使用小波逆变换返回3个通道；最后将3个通道还原成彩色图像。结果表明，该方法和传统方法相比较，可以有效保持图像的边缘特征，达到增强效果。以樟子松微观横截面为例，峰值信噪比PSNR提高了5.05，信息熵提高了3.14。本研究同时采集了榆木微观横截面、杨木宏观横截面和云杉微观横截面，其图像均得到增强。
Abstract:
 With the popularization of color image,people generally suffer from its unclearness and poor contrast in real life.In this paper,a new color image enhancement algorithm was proposed based on the RGB model,and it was then applied to the wood images.The color wood image was decomposed into three RGB channels.First,a filter was used to decompose the three channels into high-and low-frequency subbands; then the jagged detection was performed by using the Fourier transform and the wavelet transform,and the threshold value was judged.The saw tooth detected were eliminated,the low-and high frequency subbands were eliminated by a direction-adaptive filter,and a wavelet contraction function,respectively; then the wavelet inverse transform was used to return three channels; finally the three channels were restored to a color image.Compared with the traditional method,this method could effectively maintain the edge features of the image and achieve the enhanced effect.Taking the Pinus sylvestris microscopic cross section as an example,the peak signal-to-noise ratio (PSNR) increased by 5.05 and the information entropy increased by 3.14.The microscopic cross sections of eucalyptus,the macro cross section of poplar,and the microscopic cross section of spruce were also collected to increase the experimental results.

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备注/Memo

备注/Memo:
 收稿日期：2018-06-04修回日期：2018-11-20
基金项目：国家自然科学基金（31460168）。
作者简介：马坤，男，硕士在读，研究方向：图像处理技术在木材科学中的应用。E-mail：757368702@qq.com
*通信作者：多化琼，女，教授，博士生导师，研究方向：木材科学与技术。E-mail：duohuaqiong@163.com
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