Remote sensing image compression and encryption based on block compressive sensing and 2D-LCCCM

This paper proposes a remote sensing image compression and encryption algorithm based on block compressive sensing and multiple S-boxes that utilize a novel hyperchaotic system. Specifically, given that remote sensing images are large-sized, we develop a block compression-encryption algorithm comprising our novel hyperchaotic system combined with block compressive sensing. The proposed hyperchaotic system involves a two-dimensional Logistic coupling Cubic map that couples Logistic map and Cubic map. Compared to existing chaotic systems, the proposed has better ergodicity, randomness, and hyperchaotic characteristics. Moreover, to improve plaintext correlation, the block built-in scrambling and S-box substitution combine the plaintext-related weight sequence in the encryption stage, with each image block using different S-boxes to enhance the algorithm's randomness. The experimental results highlight that the proposed algorithm affords a good encryption effect, reconstruction accuracy, and anti-attack ability, especially in resisting cropping attacks.