摘要：Contourlet transform is an effective solution to solve two or more dimensional singularity and has good direction and anisotropy. Against the shortage of ability of describing the spatial distribution characteristic of object’s edge information, this paper proposed a new image retrieval algorithm based on Contourlet transform, which blocks the indexed image and decomposes each sub-block images using Contourlet transform. At first, carry out weighted processing for sub-band data of each sub-block image, extract features with high classification ability from high and low frequency sub-band data, and give greater weight for those features with high classification ability. Then, according to the energy of each sub-block image, give greater weight for those sub-block image with strong texture characteristic. At last, retrieve the images using weighted Euclidean distance between two image feature vectors as image similarity. The experiment results show that our algorithm has good retrieval performance.
