A novel meaningful image encryption algorithm based on newly-designed coupled map lattice and adaptive embedding

Abstract

In this paper, a novel visually meaningful encryption algorithm is proposed by combining ILCM-Dynamic Coupled Map Lattice (IDCML), compressive sensing (CS), and adaptive embedding. First, the 2D discrete wavelet transform (DWT) is adopted to sparse the plain image. Then the sparse matrix after threshold processing is scrambled by Fisher-Yates confusion, and the key-controlled partial Hadamard matrix is used for measurement. Finally, the gray level co-occurrence matrix (GLCM) is used to analyze the texture complexity of the carrier image for adaptive embedding, and the final visually meaningful cipher image is obtained. Compared with traditional encryption algorithms that generate noise-like cipher images, visual image encryption achieves the dual protection of digital images in content and vision, and adaptive embedding also avoids the problem that improper embedding location will affect the quality of encryption and decryption. To achieve higher security, a new combined ICMIC and Logistic chaotic map (ILCM) is first presented, then a novel ILCM dynamic coupling mapping lattice with ILCM as dynamic coupling coefficient is proposed and used in the process of compression, encryption and embedding. The experimental results and comprehensive analyses demonstrate that the proposed encryption algorithm has superior visual security and decryption quality.