Hybrid Block Chaotic Compressive Sensing and Chaotic Scrambling Algorithms for Color Image Encryption System

This paper suggests a new image encryption algorithm based on block compressive sensing (BCS) and chaotic scrambling techniques. With compressive sensing (CS), signals can be sampled much lower than the Nyquist-Shannon rate while preserving their information content. BCS can be used as a one-step process by using a 3D logistic chaotic map, the measurement matrix is used as a secret key for encryption. BCS algorithm used an individual image reconstruction algorithm that leverages l_1norm minimization to promote signal sparsity, and a smoothing operator to enhance image quality. An encrypted image is first decomposed into three sub-images based on the tricolor theory; then, a discrete wavelet transform is used to sparsely process the three decomposed images. A 2D Henon map is used to scramble the compressed image after compression. This process further enhances the security of the system by increasing the complexity of the encryption process. The results showed that the proposed system provides better security and has a lower computational complexity than other methods. Furthermore, the proposed system is resistant to known attacks such as brute force and statistical attacks.