提出一种基于双树轮廓波变换的纹理图像检索方法。双树轮廓波由塔型双树方向滤波器组构建，它保持了轮廓波灵活的方向选择性，同时克服了传统轮廓波不具有移不变性的缺点。根据双树轮廓波系数的统计特性，本文利用广义高斯分布对各子带进行建模，采用矩估计法提取模型参数，并用KL 距离度量图像之间的相似度，实现纹理图像检索。为评价检索性能，从Brodatz 图库创建了包含800 幅纹理图像的数据库。实验结果表明，本文算法的平均检索率比基于小波和轮廓波的方法分别提高了10.46%和6.94%，而且保持了较高的计算效率。

A texture image retrieval approach based on Dual-tree Contourlet (DT-Contourlet) transform is proposed. DT-Contourlet is constructed by the pyramidal dual-tree directional filter bank. It maintains the flexibility direction selectivity of the contourlet transform, and overcomes the limitation of traditional contourlet which namely lacks of shift invariance．According to the statistical characteristics of DT-Contourlet coefficients, each subband is modeled by generalized Gaussian distribution, and the moment estimator is used to extract model parameters. Finally, the texture image retrieval is implemented by computing the Kullback–Leibler Distance (KLD) between estimated models. To evaluate the retrieval performance, texture database including 800 texture images from Bradatz album is created. Experimental results indicate that, compared with traditional approaches based on wavelet and contourlet, the proposed approach improves average retrieval rate with 10.46% and 6.94% respectively and retains high computational efficiency.