Spectral Unmixing Through Gaussian Synapse ANNs in Hyperspectral Images
作者： J. L. Crespo , R. J. Duro , F. López Peña
DOI: 10.1007/978-3-540-30132-5_91
关键词:
摘要: The work presented here is concerned with the application of Gaussian Synapse based Artificial Neural Networks to spectral unmixing process when analyzing hyperspectral images. This type networks and their training algorithm will be shown very efficient in determination abundances different endmembers present image using a small set that can obtained without any knowledge on proportions present. are tested benchmark artificially generated images containing five spatially diverse finally verified real image.
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