Multiscale texture classification and retrieval based on magnitude and phase features of complex wavelet subbands
Multiscale texture classification and retrieval based on magnitude and phase features of complex wavelet subbands
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DOI：
10.1016/j.compeleceng.2011.06.008
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发表时间：
2011-09-01
影响因子：
4.3
通讯作者：
Tjahjadi, Tardi
中科院分区：
文献类型：
--
作者：
Celik, Turgay;Tjahjadi, Tardi
本文提出了一种多尺度纹理分类器，它使用的特征提取的双树复小波变换分解的纹理图像的不同分辨率的子带的幅度和相位响应。变换域中的均值和熵用于形成特征向量。所提出的方法可以实现高的纹理分类率，即使在训练阶段使用少量的样本。这使得它适用于训练中使用的纹理样本数量非常有限的应用。所提出的分类器的上级性能和鲁棒性的分类和检索图像数据库中的纹理图像。(C)2011爱思唯尔有限公司保留所有权利。
This paper proposes a multiscale texture classifier which uses features extracted from both magnitude and phase responses of subbands at different resolutions of the dual-tree complex wavelet transform decomposition of a texture image. The mean and entropy in the transform domain are used to form a feature vector. The proposed method can achieve a high texture classification rate even for small number of samples used in training stage. This makes it suitable for applications where the number of texture samples used in training is very limited. The superior performance and robustness of the proposed classifier is shown for classifying and retrieving texture images from image databases. (C) 2011 Elsevier Ltd. All rights reserved.