Contourlet transform is better in direction information representation than wavelet transform which has been studied in retrieval systems and has been shown that it is superior to wavelet ones at retrieval rate. In order to improve the retrieval rate further, an anti-aliasing contourlet-S transform based texture image retrieval system was proposed. In this system, the contourlet transform was constructed by anti-aliasing non-subsampled Laplacian pyramid cascaded by critical sub-sampled directional filter banks, sub-bands energy and standard deviations in contourlet domain are cascaded to form feature vectors, and the similarity metric used here is Canberra distance. Experimental results show that contourlet-S transform based image retrieval system is superior to those of the original contourlet transform, and non-subsampled contourlet system under the same system structure with almost same dimension of feature vectors, retrieval time and memory needed; and contourlet decomposition structure parameters can make significant effects on retrieval rates, especially scale number. To improve the retrieval rate of this system, kurtosis in each sub-band coefficients can be incorporated in features at the cost of some higher dimension of feature vectors.
