EndNet: Sparse AutoEncoder Network for Endmember Extraction and Hyperspectral Unmixing.

IEEE Transactions on Geoscience and Remote Sensing(2019)

Cited 134|Views49
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Abstract
Data acquired from multichannel sensors are a highly valuable asset to interpret the environment for a variety of remote sensing applications. However, low spatial resolution is a critical limitation for previous sensors, and the constituent materials of a scene can be mixed in different fractions due to their spatial interactions. Spectral unmixing is a technique that allows us to obtain the mate...
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Key words
Hyperspectral imaging,Neural networks,Standards,Decoding,Microscopy,Spatial resolution
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