关键词: 改进的Contourlet变换, 建模, L1能量, 广义高斯分布, 互补特征, 纹理图像检索

Abstract: Because the performance of the image retrieval system could be effectively improved by using the complementary features, a retrieval method of the texture image using L1 energy and generalized Gaussian distribution parameter features was proposed in the improved Contourlet transform domain. Firstly, the directional subband coefficients went through generalized Gaussian modeling with an improved approach. Then, the texture images were respectively retrieved based on the single feature and the corresponding similarity measurement. Lastly, using the complementary features and the direct summation of their similarity measurements, the texture images were retrieved. The experimental results show that, compared with single feature, the average retrieval rates of the texture image database are effectively improved by the complementary features that fully represent the structural information and the random distribution information.

Key words: improved Contourlet transform, modeling, L1 energy, generalized Gaussian distribution, complementary feature, texture image retrieval