Abstract
Recently, Li et al. proposed a data hiding method based on pixel value ordering (PVO) and prediction error expansion (PEE). In their method, maximum and minimum values were predicted and the pixel values were modified to embed secret data. Thereafter, many scholars have proposed improvisations to the original PVO method. In this paper, a Reversible data hiding (RDH) method is proposed where the secret data is dispersed into two layers using different modes of operations. The second layer changes the dividing mode, and the first and the second layers do not take duplicate blocks. Under a fixed embedding capacity, threshold value and block size are controlled, complex blocks are filtered and the secret data is hidden in smooth blocks. This paper also compares the effectiveness of four well-known PVO series methods, the latest PVO methods, difference expansion (DE) method and reduced difference expansion (RDE) method. Experimental results show that the proposed method reduces distortion in the image, thereby enhancing the visual symmetry/quality compared to previous state-of-the-art methods and increasing its high application value.
Highlights
In order to ensure secure data transfer over the Internet, data hiding methods are commonly used to embed secret data into cover media [1]
We used MATLAB R2018a software to execute the algorithm on WINDOWS 10 64-bit system
Based on difference expansion (DE) and reduced difference expansion method (RDE) methods, we suggest using different dividing modes to prevent taking the same block as the first layer
Summary
In order to ensure secure data transfer over the Internet, data hiding methods are commonly used to embed secret data into cover media (e.g., text, images, video) [1]. In 2003, Tian proposed difference expansion (DE) [5] which hid secret data in the difference value between adjacent pixel values It achieved high embedding capacity while keeping the distortion low. The advantage of the PPVO method was that the pixels in smooth image regions were used to embed secret data, most of which were neglected previously in PVO method due to the block constraint. Proposed an overlapping PVO method in order to enhance embedding capacity by two times as compared to the previous methods [20] This method took advantage of the correlation between adjacent pixels in natural images to increase the embedding capacity. A two-layer embedding strategy is proposed to further enhance the image quality by improving the levels of image distortion of the related PVO and DE methods.
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