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Probabilistic topic models have has successfully been used to classify remote sensing images in unsupervised way. However, the relationship among pixels is ignored in these applications because of the assuption of “bag of words”. This assuption leads to “pepper and salt effect” when these models are used to classify Very High Resolution (VHR) remote sensing images. To solve this problem, a novel model...
Typically, object-based classification methods are learned using training samples with labels attached to image objects. In this letter, a semisupervised object-based method in the framework of topic modeling is proposed to classify very high resolution panchromatic satellite images using partially labeled pixels. In the stage of training, both topics and their co-occurred distributions are learned...
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