The Alexandria project has been initiated to build a digital library for map and satellite images. Designed for content-based retrieval, the relevant information in each image is encoded in the form of a multi-dimensional feature vector. Though representing images by feature vectors~ eatly facilitates user queries, indexing these vectors degrades performance when the number of dimensions is large. We consider 2 popular techniques(DFT and SVD) to reduce the dimension of feature vectors, and study their retrieval performance with respect to recall and precision. We End that though SVD generally out-performs DFT, DFT comparesfavorably in alimited range suitable for browsing large image databases.