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RSS FeedsRemote Sensing, Vol. 11, Pages 1954: A Novel Hyperspectral Image Classification Pattern Using Random Patches Convolution and Local Covariance (Remote Sensing)

 
 

20 august 2019 17:00:23

 
Remote Sensing, Vol. 11, Pages 1954: A Novel Hyperspectral Image Classification Pattern Using Random Patches Convolution and Local Covariance (Remote Sensing)
 




Today, more and more deep learning frameworks are being applied to hyperspectral image classification tasks and have achieved great results. However, such approaches are still hampered by long training times. Traditional spectral–spatial hyperspectral image classification only utilizes spectral features at the pixel level, without considering the correlation between local spectral signatures. Our article has tested a novel hyperspectral image classification pattern, using random-patches convolution and local covariance (RPCC). The RPCC is an effective two-branch method that, on the one hand, obtains a specified number of convolution kernels from the image space through a random strategy and, on the other hand, constructs a covariance matrix between different spectral bands by clustering local neighboring pixels. In our method, the spatial features come from multi-scale and multi-level convolutional layers. The spectral features represent the correlations between different bands. We use the support vector machine as well as spectral and spatial fusion matrices to obtain classification results. Through experiments, RPCC is tested with five excellent methods on three public data-sets. Quantitative and qualitative evaluation indicators indicate that the accuracy of our RPCC method can match or exceed the current state-of-the-art methods.


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79 viewsCategory: Geology, Physics
 
Remote Sensing, Vol. 11, Pages 1955: Automatic Extrinsic Self-Calibration of Mobile Mapping Systems Based on Geometric 3D Features (Remote Sensing)
Remote Sensing, Vol. 11, Pages 1953: Direct, ECOC, ND and END Frameworks--Which One Is the Best? An Empirical Study of Sentinel-2A MSIL1C Image Classification for Arid-Land Vegetation Mapping in the Ili River Delta, Kazakhstan (Remote Sensing)
 
 
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