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Classification is one of the most important procedures in the chain of extracting Land Use/Land Cover (LU/LC) information from remote sensing imagery. How to improve the classification accuracy is the key problem that has long bedeviled the researchers. Therefore, many new classification methods and technologies have been developed, such as the Artificial Neural Network classification, the Fuzzy classification,...
Using the Quickbird remote sensing image of coastal zone of Yalu River mouth, this paper introduces the conception of separating layers, puts forward a high resolution remote sensing classification method of land use by integrating Maximum Likelihood, principal components analysis and band math. Its classification precision of water, mudflat and plough land are all higher than 80%, and the classification...
This paper presents and evaluates the use of the maximum mutual information criterion to textural feature selection for satellite image classification. Our approach is based on a recent work of Mutual Information Feature Selector Algorithm. The effectiveness of the proposed approach is evaluated on real data. In fact, the textural features are extracted using the cooccurrence matrix from two forest...
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