A sparse coding method for spectral images based on tensor dictionary learning
Different from traditional RGB images,spectral images contain additional continuous spectral curves,these information plays an important role in target recognition,target classification and other fields.However,when the spectral resolution is high,the amount of spectral image data increases dramatically and will take up more storage space.This makes it difficult to store and transmit spectral images.In this paper,a sparse coding method for spectral images based on tensor dictionary learning is proposed.By representing spectral images in tensor form,the spatial correlation between data is enhanced.Under the premise of ensuring that the image is not distorted,a priori spectral dictionary is used to perform sparse coding on spectral images.By storing this sparse coding instead of the original data,the storage capacity of spectral images is reduced.
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