基于小波多通道特征级融合的彩色纹理图像分析

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

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 2 0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

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.