Spectral Image Compressed Sensing Reconstruction Based on Tensor Decomposition
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.
万方数据
维普
