A joint model of complex wavelet coefficients for texture retrieval

We present a Copula-based statistical model of complex wavelet coefficient magnitudes for color texture image retrieval. Our model is based on two-parameter Weibull distributions and a multivariate Student t Copula. For similarity measurement we employ a Monte- Carlo approach to approximate the Kullback-Leibler divergence between two models. The experimental retrieval results show that the incorporation of the dependency structure between subbands significantly improves retrieval accuracy compared to previous approaches.