A visually secure image encryption scheme based on adaptive block compressed sensing and non-negative matrix factorization

Abstract

The traditional block compressive sensing theory cannot make full use of the difference of image block information characteristics for sampling, and the measurement matrix cannot fully measure the image according to the image block information characteristics. To solve these problems, we design an adaptive block compressed sensing (ABCS) algorithm, and we propose a visually secure image encryption scheme based on ABCS and non-negative matrix factorization (NMF). First, the plain image is decomposed by Tetrolet transform. Then, we perform matrix shuffling to optimize the sparsity of the sparse matrix. Next, adaptive sampling and measurement are performed according to the information distribution characteristics between the image blocks to compress the image to a quarter of its original size. Last, we design a scrambling–diffusion framework based on tetrominoes to obtain the secret image, which is then embedded into the carrier image by means of NMF to obtain a visually secure cipher image. The experimental results show that the proposed scheme can consider the security of image information transmission and the integrity of reception, and has good resistance to various attacks.