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We hide grayscale secret images into a grayscale cover image, which isconsidered to be a challenging steganography problem. Our goal is to develop asteganography scheme with enhanced embedding capacity while preserving thevisual quality of the stego-image as well as the extracted secret image, andensuring that the stego-image is resistant to steganographic attacks. The novelembedding rule of our scheme helps to hide secret image sparse coefficientsinto the oversampled cover image sparse coefficients in a staggered manner. Thestego-image is constructed by using ADMM to solve the LASSO formulation of theunderlying minimization problem. Finally, the secret images are extracted fromthe constructed stego-image using the reverse of our embedding rule. Usingthese components together, to achieve the above mentioned competing goals,forms our most novel contribution. We term our scheme SABMIS (SparseApproximation Blind Multi-Image Steganography).  We perform extensive experiments on several standard images. By choosing thesize of the secret images to be half of the of cover image, we obtain embeddingcapacities of 2 bpp (bits per pixel), 4 bpp, 6 bpp, and 8 bpp while embeddingone, two, three, and four secret images, respectively. Our focus is on hidingmultiple secret images. For the case of hiding two and three secret images, ourembedding capacities are higher than all the embedding capacities obtained inthe literature until now. For the case of hiding four secret images, althoughour capacity is slightly lower than one work, we do better on the other twogoals; a) very little deterioration in the quality of the stego-images andextracted secret images, and b) inherently and designed-to-be resistant tosteganographic attacks. Additionally, we demonstrate that SABMIS executes infew minutes, and show its application on two real-life problems.

SABMIS: Sparse approximation based blind multi-image steganography scheme