The spectral imaging provides important support for ballistic missile early warning by virtue of its abundant spatial and spectral information,and the compressive sensing provides a effective approach for spectral image data collecting and processing.Aiming at the existing compressed perceptual reconstruction mostly adopts the coding method of"spatial domain compressed sampling and inter-spectral traditional compression",which still exists a certain waste of resources,a compressed perceptual reconstruction method based on tensor decomposition for spectral images is proposed.Taking use of the sparsity of spectral image data in three-dimensional space,a reconstruction model based on Tucker decomposition is built,and the solution algorithm based on orthogonal matching pursuit(OMP)is given.Moreover,an improved OMP algorithm which takes three-dimension tensors as dictionary atoms is proposed by expanding traditional OMP algorithm into three-dimensional space.The experimental results indicate that the proposed method can effectively reduce algorithm complexity and improve the performance of reconstruction.
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