基于复值小波包概率模型的纹理分类研究  

RESEARCH ON TEXTURE CLASSIFICATION BASED ON COMPLEX WAVELET PACKET PROBABILISTIC MODEL

作　　者：才德[1] 洪文[1] 吴一戎[1] 

机构地区：[1]中国科学院电子学研究所微波成像技术国家重点实验室,北京100080

出　　处：《计算机应用与软件》2008年第9期226-227,232,共3页Computer Applications and Software

摘　　要：为准确描述纹理,发挥复值小波包变换多方向通道等优点,首次基于复值小波包对纹理采用概率模型进行自适应描述,并同最大似然分类方法结合进行纹理分类。提出融合各类纹理最优描述的方法,将图库分类正确率从85%提高到93%。For accurate texture description,with the advantage of directional channel selection in dual-tree complex wavelet packet transform,the adaptive probabilistic texture model is used. With the maximum likelihood classification method, an approach which combines the best description of each texture is proposed. By this approach ,the correct rate of classification increases from 85% to 93%.

关 键 词：自适应描述 复值小波包变换 最优基选取 纹理图像分类 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术] TM711[自动化与计算机技术—计算机科学与技术]