Content-Based Color Image Retrieval Using Adaptive Lifting

An image retrieval system is a computer system for browsing, searching and retrieving images from a large database of digital images. CBIR aims at avoiding the use of textual descriptions and instead retrieves images based on their visual similarity to a user-supplied query image or user-specified image features. Although classical wavelet transform is effective in representing image feature and thus is suitable in CBIR, it still encounters problems especially in implementation, e.g. floating-point operation and decomposition speed, which may nicely be solved by lifting scheme, a novel spatial approach for constructing biorthogonal wavelet filters. Lifting scheme has such intriguing properties as convenient construction, simple structure, integer-to-integer transform, low computational complexity as well as flexible adaptivity, revealing its potentialsin CBIR. In this paper, by using general lifting and its adaptive version, we decompose HSI color images into multi-level scale and wavelet coefficients, with which, we can perform image feature extraction.