کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
4948512 1439615 2016 20 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Multispectral image classification based on improved weighted MRF Bayesian
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
پیش نمایش صفحه اول مقاله
Multispectral image classification based on improved weighted MRF Bayesian
چکیده انگلیسی
This paper presents a novel nonparametric supervised spectral-spatial classification method for multispectral image. In multispectral images, if an unknown pixel shows similar digital number (DN) vectors as pixels in the training class, it will obtain higher posterior probability when assuming DN vectors of different classes follow a certain type of statistical distribution. According to statistical characteristics about DN vectors, the proposed method assumes the vectors follow a Gaussian mixture distribution in each class. Particularly, adaptively Bayesian nonparametric method is developed to estimate the optimal settings in distribution model appropriately. Then, we construct an anisotropic hierarchical logistic spatial prior to capture the spatial contextual information provided by multispectral image. Finally, optimized simulated annealing algorithm is conducted to estimate the maximum a posteriori. The proposed approach is compared with state-of-the-arts classification methods of multispectral images. The comparison results suggested that the proposed approach outperformed in overall accuracy and kappa coefficient.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Neurocomputing - Volume 212, 5 November 2016, Pages 75-87
نویسندگان
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