Automatic Annotation of Multispectral Satellite Images Using Author–Topic Model

In this letter, we propose a new method for the annotation of multispectral satellite images. This method performs the multispectral image annotation by incorporating a graphical model. To obtain the annotated image, first, we use a set of images with defined semantic concepts to represent the training set. Second, the images are represented by several visual words based on the color and texture features. Finally, an author-topic model is exploited to estimate probabilities of semantic classes for the regions in the test images and categorize them into the semantic concepts. Experimental evaluation on the multispectral images demonstrates the good performance of the proposed method on the multispectral image annotation.