Hyperspectral Image Classification with Markov Random Fields and a Convolutional Neural Network

1 May 2017Xiangyong CaoFeng ZhouLin XuDeyu MengZongben XuJohn Paisley

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... (read more)

PDF Abstract
TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK RESULT LEADERBOARD
Hyperspectral Image Classification Indian Pines CNN-MRF Overall Accuracy 96.12% # 4
Hyperspectral Image Classification Pavia University CNN-MRF Overall Accuracy 96.18% # 5

Methods used in the Paper


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