High-Capacity Data Hiding Method Based on Two Subgroup Pixels-Value Adjustment Using Encoding Function

Abstract

Confidential information can be hidden in digital images through data hiding technology. This has practical application value for copyright, intellectual property protection, public information protection, and so on. In recent years, researchers have proposed many schemes of data hiding. However, existed data hiding schemes suffer from low hiding capacity or poor stego-image quality. This paper uses a new method of multiple pixels-value adjustment with encoding function (MPA) to further improve the comprehensive performance, which is well in both hiding capacity and stego-image quality. The main idea is to divide n adjacent cover pixels into two sub-groups and implement multi-bit-based modulus operations in each group, respectively. The efficacy of this proposed is evaluated by peak signal-to-noise ratio (PSNR), embedding payload, structural similarity index (SSIM), and quality index (QI). The recorded PSNR value is 30.01 dB, and embedding payload is 5 bpp (bits per pixel). In addition, the steganalysis tests do not detect this steganography technique.

A Fast and Low Distortion Image Steganography Framework Based on Nature-Inspired Optimizers

“…By comparing the proposed framework to the benchmark method MPA [24] and alternative additional methods, the performance of the proposed framework is evaluated. A number of engineering metrics are used to assess the quality of the image, illustrated as follows.…”

“…By deploying inverse operations on the stego image, invertible neural networks will recover the information. To further improve the hiding capacity and the quality of the stego images, [24] introduces a multiple pixel-value adjustment (MPA) scheme with an encoding function. Multi-bit modulus operations are performed within each group of adjacent host pixels after splitting N adjacent pixels into two subgroups.…”