In this paper, we present a model to define an analogy between text and image data using ICA basis functions and we
apply it to index Very High Resolution (VHR) satellite images. We introduce our text-image analogy by defining visual
documents, visual words, visual vocabulary and labeling each word of document using vocabulary words. Further, we
propose a classification using a simple Bayesian method to evaluate our model for VHR satellite image characterization.
The results for two types of vocabularies, one based on visual words clustering and other based on obtaining ICA
components for each class, is compared for a variety of natural and man-made scenes.
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