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基于小波多通道特征级融合的彩色纹理图像分析
引用本文:李明,吴艳,吴顺君.基于小波多通道特征级融合的彩色纹理图像分析[J].光子学报,2004,33(8):999-1003.
作者姓名:李明  吴艳  吴顺君
作者单位:1. 西安电子科技大学雷达信号处理国家重点实验室,西安,710071
2. 西安电子科技大学雷达信号处理国家重点实验室,西安,710071;西安电子科技大学电子工程学院,西安,710071
基金项目:国家重点实验室基金资助项目 (5 14 310 2 0 2 0 4DZ0 1)
摘    要:在不完全树型小波分解基础上将纹理和颜色特征进行融合,提出了适合彩色纹理图像分析的新的特征,它比单纯的灰度纹理特征或颜色特征具有更强的分类能力.同时还利用20类真实彩色自然纹理图像对塔式小波分解、不完全树型小波分解和小波包分解进行了多特征融合的分类比较,实验结果表明:不完全树型小波分解的特征级融合表现出良好的分类性能和抗噪能力.

关 键 词:纹理  颜色  特征级融合  不完全树型小波分解
收稿时间:2004-02-01

Colored Texture Analysis of Feature-level Fusion Based on Multichannel Wavelet Decomposition

.Colored Texture Analysis of Feature-level Fusion Based on Multichannel Wavelet Decomposition[J].Acta Photonica Sinica,2004,33(8):999-1003.
Authors:
Institution:(1 National Key Lab. of Radar Signal Processing ,Xidian Univ.,Xi’an 710071)
(2 School of Electronics Engineering,Xidian Univ,Xi’an 710071)
Abstract:A new algorithm is developed to represent colored texture by effectively merging both the texture and color information based on Incomplete Tree-Structured Wavelet Decomposition,which has even better classification performance than single texture or color feature. Experiments are conducted on a set of 20 natural colored texture images in which the classification of feature-level fusion can be performed on the basis of Pyramid Wavelet Decomposition (PWD),In-Complete Tree-Structured Wavelet Decomposition (ICTSWD) and wavelet packet decomposition (WPD). It is demonstrated that colored texture feature based on ICTSWD has better classification performance and anti-noise ability than other features based on PWD and WPD.
Keywords:Texture  Color  Feature-level fusion  Incomplete tree-structured wavelet decomposition
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