The primary goal of steganographic methods is to develop statically undetectable methods with high steganographic capacity. The embedding efficiency is one kind of measure for undetectability. Block-based steganography methods have been proposed for achieving higher embedding efficiency under limited embedding capacity. However, in these methods, some blocks with larger embedding distortions are skipped, and a location map is usually incorporated into these methods to record the embedding status of each block. This reduces the embedding capacity for secret messages. In this study, we proposed a block-based steganography method without a location map for palette images. In this method, multiple secret bits can be embedded in a block by modifying at most one pixel with minimal embedding distortion; this enables each block to be used for data embedding; thus, our method provides higher embedding capacity. Furthermore, under the same capacity, the estimated and experimental embedding efficiencies of the proposed method are compared with those of Imaizumi et al. and Aryal et al.’s methods; the comparisons indicate that the proposed method has higher embedding efficiency than Imaizumi et al. and Aryal et al.’s methods.
In view of the technique “A New Histogram Modification Based Reversible Data Hiding Algorithm Considering the Human Visual System” by Jung et al., some modifications have been made on the parts of the causal window and the pixel overflow/underflow in present study. In Jung et al.’s method, the number of reference pixel was obtained based on a causal window so that the prediction value, the just noticeable difference (JND) and others can be determined. However, the causal window used in Jung et al.’s method may reduce the prediction accuracy. In this paper, the modifications on two parts are proposed to turn around this situation. First, the causal window is narrowed to decrease the number of reference pixels so that the prediction accuracy can be enhanced. Second, in dealing with possible pixel underflow or overflow, only the pixels that will definitely underflow or overflow, are modified. Using such modifications both the payload and the image quality can be improved. It is shown by experiments that our modifications not only increase payload but also maintain image quality effectively.
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