A multispectral image compression and encryption algorithm based on tensor decomposition and chaos

A multispectral image compression and encryption algorithm that combines Karhunen-Loeve (KL) transform,tensor decomposition and chaos is proposed for solving the security problem of multi-spectral image compression and transmission. Firstly, in order to eliminate residual spatial redundancy and most of the spectral redundancy, the image is performed by KL transform. Secondly, to further eliminate spatial redundancy and reduce block effects in the compression process, two-dimensional discrete 9/7 wavelet transform is performed, and then Arnold transform and encryption processing on the transformed coefficients are performed. Subsequently, the tensor is decomposed to keep its intrinsic structure intact and eliminate residual space redundancy. Finally, differential pulse filters are used to encode the coefficients, and Tent mapping is used to implement confusion diffusion encryption on the code stream. The experimental results show that the method has high signal-to-noise ratio,fast calculation speed, and large key space, and it is sensitive to keys and plaintexts with a positive effect in spectrum assurance at the same time. Copyright © by HIGH TECHNOLOGY LETTERS PRESS.