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The polarimetric Synthetic Aperture Radar (POLSAR) image data has the problems of the noisy pixels and vague category boundaries because of its complex scattering mechanism and statistical property, which strongly influence the classification quality, while the fuzzy possibilistic C-means (FPCM) is robust in detecting the noisy pixels and modeling the uncertainty. Hence, we tried FPCM algorithm combined...
Supervised classification of fully polarimetric SAR image using neural network is a common method nowadays. As an effective learning method of neural network, BP algorithm is the most widespread one in the neural network algorithms. However, BP network is easy to fall into local extremum and exists shortcomings such as the slow training process. To this end, this paper presents a method of supervised...
This paper analyses the visual characteristics of ground buildings in high resolution SAR images: the L-shaped echoes resulted from layer over and corner reflection effects give expression to the information of location and height of buildings. Therefore, to vectorize the L-shaped outline of the buildings has a great value in the field of city mapping. Focusing on L-shaped echoes, this paper investigates...
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