Abstract
Reversible data hiding (RDH) methods are widely used in many privacy-sensitive real-time applications for digital images. As an efficient RDH method, prediction-error histogram (PEH) shifting technique has found wide application for its high efficiency in increasing embedding capacity. Nowadays, the performance of most PEH-based methods is evaluated only by Peak Signal to Noise Ratio (PSNR) or Structural Similarity (SSIM) Index. However, more and more applications require high quality in both PSNR and SSIM. Therefore, in this paper, we propose a new RDH method to concentrate on both PSNR and SSIM performance, which involves two key techniques: 1) an SSIM-based block selection technique, 2) a PEH-based optimal expansion bins selection technique. Through block selection, the original image is divided into two parts: smooth blocks and rough blocks. We select pixels of smooth block for double embedding and leave pixels of rough block unchanged. According to the optimal expansion bins, reasonable pixels are chosen for embedding such that the embedding distortion can be reduced. With these improvements, our proposed method has higher SSIM and PSNR after embedding compared to other PEH-based methods. The experimental results demonstrate its superiority over some state-of-the-art counterpart and other conventional PEH-based works.
Highlights
With the fast development and wide application of Internet technology, the amount of information is increasing dramatically
We simple point out auxiliary information which is necessary in our scheme
This Structure Similarity (SSIM)-based block selection ensures that the local structural similarity of the image remains stable after prediction and prevents more damage on structure and visual quality caused by further data embedding
Summary
With the fast development and wide application of Internet technology, the amount of information is increasing dramatically. Have the disadvantage of low embedding capacity and may lead to severe degradation of image quality In this light, more efficient RDH methods have been proposed to achieve better performance, such as difference expansion (DE) [5]–[10] and histogram shifting (HS) [11]–[15]. Wang et al.: RDH Based on SSIM Block Selection the pixels at peak bin are used for embedding one bit data and those bins between two bins are shifted one step towards zero bin to create vacancies According to such principle, the performance of HS-based schemes heavily depends on the determination of the peak and zero bins as well as the sharpness of the generated histogram. In [40], the author proposed an optimal RDH algorithm under structural similarity constraint These methods mainly paid attention to reduce structure distortion or improve visual quality without considering PSNR and embedding capacity.
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