Abstract: In general, a data hiding technique for digital content can be classi?ed into data embedding and perceptual encryption (Scrambling). Data embedding techniques focuses on high-output image quality so that the difference between the original and the embedded images is imperceptible to the naked eye. As a new trend some researcher explores the reversible data embedding technique to get higher payload on the cost of degradation in perceptual quality of the output image. This paper proposed a unique technique i.e Uni?ed data embedding-scrambling technique called UES to achieve two objectives simultaneously, namely, high payload and adaptive scalable quality degradation. First Checkerboard based prediction method is proposed for pixel intensity value prediction. In this method 75% of the pixel is predicted with reference to information obtained from 25% of the image. Then based upon prediction error calculated, locations of predicted pixels are vacated to embed information. In addition, the prediction errors are stored at a predetermined precision using the structure side information to perfectly reconstruct or approximate the original image. The precision of the stored prediction errors can be adjusted to control the perceptual quality of the reconstructed image. Experimental results confirm that the proposed UES algorithm is able to reconstruct the original image after completely degrading its perceptual quality.
Keywords: Data hiding, Embedding, Scrambling, Precision error.