Content-adaptive image compression and encryption via optimized compressive sensing with double random phase encoding driven by chaos

Abstract With the advancement of multimedia technology and coming big data era, size image is significantly increased. However, traditional encryption methods cannot solve emerging problems efficient compression. To settle with this challenge, an effective content-adaptive compression method based on compressive sensing double random phase encoding (DRPE) proposed in paper. The original converted to one low-frequency part three high-frequency parts by DWT then permutated sorting-based chaotic sequences. Afterward, a novel measurement matrix optimization algorithm adaptive step presented measure components. enhance security scheme, DRPE, quantization, diffusion are successively performed complex composed shuffled component value matrices obtain cipher image. Logistic-Sine system utilized produce keystreams for process, its parameter initial determined information entropy plain external key parameters, so that can withstand known-plaintext chosen-plaintext attacks effectively. Numerical experiments demonstrate effectiveness algorithm.