一种基于小波突出点颜色及空间分布熵的图像检索方法

分析了基于兴趣点的图像检索方法的缺点，提出了一种基于小波突出点的图像检索新方法．该方法在小波域提取突出点，这些突出点既表示了全局变化也表示了局部变化；然后以小波突出点为线索，设计了基于小波突出点的颜色分布熵，既利用了小波突出点的局部特征，又考虑了小波突出点的空间分布结构；用图像间的颜色分布熵来度量图像间的相似性．该检索算法不但保证了对图像旋转、平移鲁棒性，而且克服了传统直方图没有空间位置的缺陷．实验结果表明，该方法对图像检索是有效的．

A novel image retrieval algorithm based on color and distribution entropy of wavelet salient points

Having analyzed the drawbacks of image retrieval based on interest points, a novel image retrieval algorithm is proposed in this paper.using wavelet-based salient points. The algorithm extracts the salient points in wavelet domain and these salient points not only represent global variations as well as local variations; then the salient points are regarded as clues and color distribution entropy is designed, which takes not only the local color feature into consideration, but also the space distribution information of the salient points. The similarities are measured by the distance of color distribution entropy. With robustness to rotation and translation, the algorithm avoids the shortcoming of losing the location information in the traditional color histogram. Experimental results show that this algorithm is efficient for image retrieval.