Abstract
The technique of reversible data hiding enables an original image to be restored from a stego-image with no loss of host information, and it is known as a reversible data hiding algorithm (RDH). Our goal is to design a method to predict pixels effectively, because the more accurate the prediction is, the more concentrated the histogram is, and it minimizes shifting to avoid distortion. In this paper, we propose a new multi-directional gradient prediction method to generate more accurate prediction results. In embedding stage, according to the embedding capacity of information, we generate the best decision based on non-linear regression analysis, which can differentiate between embedding region and non-embedding region to reduce needless shifting. Finally, we utilize the automatic embedding range decision. With sorting by the amount of regional variance, the easier predicted region is prior for embedding, and the quality of the image is improved after embedding. To evaluate the proposed reversible hiding scheme, we compared other methods on different pictures. Results show that the proposed scheme can embed much more data with less distortion.
Highlights
Reversible data hiding (RDH) approach has been applied to some sensible and crucial messages, such as medical images, military pictures, criminal site pictures, digital files of rare artworks
After studying the algorithms that were developed by previous RDH researchers, we find that the embedding capacity and the image quality of embedding are quite depended on the prediction method of RDH algorithm
We find a common problem of previous algorithms for embedding, that is, in order to achieve the reversible requirement, even if the current position cannot be embedded, it would be shifted with the reversible condition, and that will lead to the distortion of image and lower the image quality after embedding
Summary
Reversible data hiding (RDH) approach has been applied to some sensible and crucial messages, such as medical images, military pictures, criminal site pictures, digital files of rare artworks. The reversible data hiding techniques have been proposed It can be divided into spatial domain [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18] and frequency domain [19, 20]. These techniques can be divided into three classifications: lossless compression, expansion based (EB), and histogram shifting (HS). RDH was based on lossless compression [1,2,3,4] These methods utilized storage space for embedding. These methods utilized storage space for embedding. [3] proposed the least significant bit (LSB) method, which increases compression efficiency by means of change in
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