Image indexing using wavelet vector quantization

In this paper, we propose a new technique based on wavelet vector quantization for the storage and retrieval of compressed images. Here, the images are first decomposed using wavelet transform followed by vector quantization of the transform coefficients. We note that similar images map to similar labels. Hence, the labels corresponding to an image constitute a feature vector which is used as an index to store and retrieve the image. In addition, the lowest resolution subimages resulting from the wavelet decomposition serve as visual icons for browsing purposes. The proposed technique provide fast access to the compressed images in the database has a lower cost for computing and storing the indices compared to other techniques reported in the literature.