With the rapid development of multimed ia and network,there have been much interest and a large number of researches on digital image.Searching image from massive network images becomes an urgent tas k.In order to reduce the effect of rotation and scale transform in the process of ret rieving,a rotation invariant retrieval algorithm based on entropy and non-subsampled contourlet transform (NSCT) is pr oposed according to the symmetry of entropy.Firstly,the image is decomposed in multi-scale and multi-direction by NSCT,and high frequency sub-bands of the same direction at different scales are multiplied to reduce the effects of scale change and noise. Secondly,because the energy proportion of each directional sub-band in the who le image is constant after image rotation,the energy proportion as probability vector and the roughness of each d irectional sub-band as weight are employed to calculate the weighted information entropy of the image,which is con sidered as the rotation-invariant texture feature of image.Color and shape features are extracted by moments.Finally,three kinds of features are normalized to analyze the similarity between two images using Euclidean distan ce.Rig orous performance tests on two databases of rotation and scale change show that the proposed algorithm is robust to rotation and scale variance,and has high precision and recall.