Adaptive embedding: A novel meaningful image encryption scheme based on parallel compressive sensing and slant transform

AbstractHighlights •A novel image encryption and adaptive embedding algorithm is proposed by combining 4D memristive hyperchaos, parallel compressive sensing (PCS) and slant transform (ST).•A lossy transform domain-based embedding method is designed to embed the unquantized cipher data into the host image to improve the decrypted quality and robustness of the algorithm.•The frequency-domain information of plain image is associated with the encryption process. Therefore, the proposed encryption algorithm has good plaintext sensitivity.•There is no need to transmit the quantization parameters as secret keys to decrypter. Additionally, the generated visually meaningful image has the same size as the plain image. It does not increase the storage space and transmission cost. Graphical abstractDisplay OmittedAbstractA novel image encryption and adaptive embedding algorithm is proposed in this paper by combining 4D memristive hyperchaos, parallel compressive sensing (PCS) and slant transform (ST). This work dedicates to balancing the performance of existing visually meaningful image encryption algorithms which embed cipher image into host image in spatial or transform domains. First, the 2D discrete wavelet transform (DWT) is adopted to sparse the plain image. Then the sparse matrix after threshold processing is encrypted and compressed through Arnold scrambling and parallel compressive sensing to obtain the cipher data. Next the noise visibility function (NVF) is utilized to find the sub-images suitable for embedding in host image. After that the unquantified cipher data are randomly embedded in them by ST-based embedding method with block-wise manner and the final visually meaningful cipher image is obtained. To withstand the chosen-plaintext attacks (CPA) and the known-plaintext attacks (KPA), the frequency-domain information of plain image is used to control the 4D memristive hyperchaos to generate the scrambling matrix. Additionally, the experimental results and comprehensive analyses demonstrate that compared with the existing related algorithms, the proposed encryption algorithm has good visual security, decryption quality and superior robustness.