Hiding Multiple Images into a Single Image Using Up-Sampling

The goal of multiple-image hiding is to hide several secret images within another carrier image without significantly changing its appearance, and then perfectly reconstruct all of the secret images. The challenge is to ensure that the stego-image has great visual quality and can resist various steganalysis under the premise of hiding as much information as possible in one image. To address this issue, the majority of known image-hiding methods focus on hiding images using compression techniques. In this paper, we present a novel multiple-image hiding method based on up-sampling and reversible color transformation. First, the interpolation algorithm up-samples the carrier image, so that the attribute of similar neighboring pixel values in the up-sampled image can significantly improve the effect of image hiding. The embedding procedure is then performed using the proposed Euclidean Distance (ED)-based block matching and reversible color transformation, which decreases the chance of local blurring in the stego-image. Experimental results show that the proposed method surpasses existing advanced methods by achieving an average of 33 dB and 28 dB of PSNR for the stego-image with a hiding capacity 2 BPP and 8 BPP, and obtaining 100% reconstructing accuracy for all secret images. It also has a high level of resistance to steganalysis and a strong robustness against various image-processing attacks.