A cluster-based appraoch to content based time series retrieval (CBTSR)

Given a user-defined image time series (i.e., the query time series), content based time series retrieval (CBTSR) is the process of identifying other time series that show properties similar to the query. When dealing with time series, the elements of the content based retrieval process require to be redefined in order to take into account the time variable. In this perspective, the design of the query, the feature extraction, and retrieval itself have to be reformulated. Here we focus our attention to CBTSR in pairs of images. The goal is to identify bi-temporal images showing a specific kind of change (associated with changes on the ground) modeled by the query. Attention is devoted to the design of the auxiliary archive modeling the change information and on the retrieval algorithm. Experiments on an archive of Landsat images confirmed the effectiveness of the proposed approach.