The present invention relates to an image retrieval method. According to the method, color features of images are extracted by using a color histogram, two features, such as a color vector of the color histogram and the height of a color column, are used as retrieving bases, the degree of similarity is calculated by using a fuzzy membership function in a fuzzy set theory, the similarity is judged by using an alpha-level fuzzy relationship, meanwhile, texture features of the images are extracted by introducing non-subsampled contourlet transform (NSCT), the images are decomposed by using the NSCT, mean values and standard variances of subband coefficients in different levels and multiple directions are extracted as feature vectors which serve as indexes of images in an image library, the degree of similarity among the images is calculated by using the fuzzy membership function in the fuzzy set theory, powerful direction information is reserved after the images are decomposed due to the multi-scalability, multi-directionality and translation invariance of the images, thus, the texture features of the images can be described more comprehensively, and finally, the images are retrieved through combining two algorithms and applying comprehensive features.