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This paper compares four commonly used fuzzy analytical methods for remote sensing digital image classification, i.e. fuzzy c-means, semi-supervised fuzzy cluster labeling, fuzzy nearest neighbor, and object-oriented fuzzy classifiers. Merits and weak points of each method were examined through a case study with a multispectral high-resolution airborne digital image of urban settings. Results showed...
This paper proposes a novel vehicle detecting approach for surveillance scenes with single stationary camera. Difference accumulative based background modeling method is used for background modeling. Background subtraction operation is used for detecting moving vehicles and Otsu method is used to threshold the background difference image. Subtractive clustering algorithm is applied for vehicle locating...
The pattern recognition of remote sensing images is based on the different spectral characteristics of surface features to identify the features type, mainly including the supervised classification and unsupervised classification. In this paper, the TM remote sensing images are preprocessed firstly, and then land-covered features are classified using the maximum likelihood method, the minimum distance...
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