An Efficient Hybrid Steganography Method Based on Edge Adaptive and Tree Based Parity Check

A major requirement for any steganography method is to minimize the changes that are introduced to the cover image by the data embedding process. Since the Human Visual System (HVS) is less sensitive to changes in sharp regions compared to smooth regions, edge adaptive has been proposed to discover edge regions and enhance the quality of the stego image as well as improve the embedding capacity. However, edge adaptive does not apply any coding scheme, and hence it embedding efficiency may not be optimal. In this paper, we propose a method that enhances edge adaptive by incorporating the Tree-Based Parity Check (TBPC) algorithm, which is a well-established coding-based steganography method. This combination enables not only the identification of potential pixels for embedding, but it also enhances the embedding efficiency through an efficient coding mechanism. More specifically, the method identifies the embedding locations according to the difference value between every two adjacent pixels, that form a block, in the cover image, and the number of embedding bits in each block is determined based on the difference between its two pixels. The incorporation of TBPC minimizes the modifications of the cover image, as it changes no more than two bits out of seven pixel bits when embedding four secret bits. Experimental results show that the proposed scheme can achieve both large embedding payload and high embedding efficiency.