Abstract
Data embedding techniques maintain high output image quality so that the difference between the original and the embedded images is unrevealed to the naked eye. Practically, this is not the case as the payload increase results in exposing that something is being hidden. In this paper, the objectives, namely, adaptive scalable quality degradation, high payload and maximum retrieval capacity are achieved using a unified data embedding-scrambling technique called UES. Pixels are predicted using Checkerboard based prediction (CBP) and the location of the predicted pixels are vacated based on the value of key to embed the secret image in the cover image after Singular Value Decomposition (SVD). The prediction errors are stored as side information to reconstruct the cover and secret image. The results are analyzed based on the values of PSNR and SSIM. The results produced show that although the stego image becomes distorted for higher key values, the reconstruction process achieves retrieval of both cover and secret image.
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