[1]范文兵,陈静,甄姬娜..图像小波系数的自相似性在图像去噪中的应用[J].郑州大学学报(工学版),2005,26(03):89-93.[doi:10.3969/j.issn.1671-6833.2005.03.024]
　FAN Wenbing,CHEN Jing,Zhen Jina.Application of self-similarity of image wavelet coefficient in image denoising[J].Journal of Zhengzhou University (Engineering Science),2005,26(03):89-93.[doi:10.3969/j.issn.1671-6833.2005.03.024]
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图像小波系数的自相似性在图像去噪中的应用()
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《郑州大学学报(工学版)》[ISSN:1671-6833/CN:41-1339/T]

卷:
26
期数:
2005年03期
页码:
89-93
栏目:
出版日期:
1900-01-01

文章信息/Info

Title:
Application of self-similarity of image wavelet coefficient in image denoising
作者:
范文兵; 陈静; 甄姬娜.
郑州大学信息工程学院,河南,郑州,450052, 郑州大学信息工程学院,河南,郑州,450052, 郑州大学信息工程学院,河南,郑州,450052
Author(s):
FAN Wenbing; CHEN Jing; Zhen Jina
关键词:
小波变换;  Mallat算法;  隐马尔科夫树模型;  图像去噪
Keywords:
DOI:
10.3969/j.issn.1671-6833.2005.03.024
文献标志码:
A
摘要:
讨论了图像小波系数的四叉树结构及统计规律,指出在四叉树各层节点的小波系数具有自相似性,利用这种自相似性建立混合高斯模型对小波系数进行描述;此外,四叉树层与层间的节点之间具有相关性,利用小波域系数间的自相似性信息和相关性建立隐式马尔科夫树模型(HMT),用于去除图像信号中的高斯白噪声,并利用Lenna图像进行试验仿真;与传统的低通滤波方法相比,该方法在滤除噪声的同时更好地保存了图像的细节和边缘信息.结论表明,隐式马尔科夫树(HMT)模型较精确的体现了图像的特征,具有较好的去噪效果.
Abstract:
The structure and statistical law of the wavelet coefficient of the image are discussed, and it is pointed out that the wavelet coefficient at each layer of the quadtree has self-similarity, and a hybrid Gaussian model is established to describe the wavelet coefficient by using this self-similarity. In addition, the four-tree layer has correlation between the nodes between the layers, and an implicit Markov tree model (HMT) is established by using the self-similarity information and correlation between the wavelet domain coefficients to remove Gaussian white noise in the image signal, and the Lenna image is used for experimental simulation. Compared with the traditional low-pass filtering method, this method can better preserve the details and edge information of the image while filtering out the noise. The results show that the implicit Markov tree(HMT) model reflects the characteristics of the image more accurately and has a better denoising effect.

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更新日期/Last Update: 1900-01-01