Hyperspectral Image Classification With Markov Random Fields and a Convolutional Neural Network.
IEEE Transactions on Image Processing(2018)
摘要
This paper presents a new supervised classification algorithm for remotely sensed hyperspectral image (HSI) which integrates spectral and spatial information in a unified Bayesian framework. First, we formulate the HSI classification problem from a Bayesian perspective. Then, we adopt a convolutional neural network (CNN) to learn the posterior class distributions using a patch-wise training strate...
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关键词
Feature extraction,Task analysis,Machine learning,Hyperspectral imaging,Bayes methods,Data mining
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