Feature extraction is a key issue in contentbased image retrieval (CBIR). In the past, a number of texture features have been proposed in literature, including statistic methods and spectral methods. However, most of them are not able to accu

1．分析研究了基于内容的图像检索系统的工作原理，关键技术如：纹 理、形状等图像底层特征的描述方法， 图像间的相似性度量方法， 图像库索引机制等。 2．研究了基于纹理特征的图像检索方法，并提出了一种基于NSCT 变 换的纹理特征提取方法。通过对SAR 图像及相关图像进行NSCT 分解，计算不同尺度不同方向上的系数幅度序列的均值，标准方差 和三阶中心矩，以此构成特征向量来描述图像的纹理。实验证明本 文提出的采用NSCT 算法有较好的特征提取效果，引入三阶中心矩 作为特

Colourhistogram II. TEXTURE FEATURE EXTRACTION IN CBIR An overview of the proposed CBIR system is illustrated in Fig. 1. The proposed algorithm, Label Wavelet Transform (LWT), is based on color image segmentation [1], and it is an extens