The image-based data hiding method is a technology used to transmit confidential information secretly. Since images (e.g., grayscale images) usually have sufficient redundancy information, they are a very suitable medium for hiding data. Absolute Moment Block Truncation Coding (AMBTC) is one of several compression methods and is appropriate for embedding data due to its very low complexity and acceptable distortion. However, since there is not enough redundant data compared to grayscale images, the research to embed data in the compressed image is a very challenging topic. That is the motivation and challenge of this research. Meanwhile, the Hamming codes are used to embed secret bits, as well as a block code that can detect up to two simultaneous bit errors and correct single bit errors. In this paper, we propose an effective data hiding method for two quantization levels of each block of AMBTC using Hamming codes. Bai and Chang introduced a method of applying Hamming (7,4) to two quantization levels; however, the scheme is ineffective, and the image distortion error is relatively large. To solve the problem with the image distortion errors, this paper introduces a way of optimizing codewords and reducing pixel distortion by utilizing Hamming (7,4) and lookup tables. In the experiments, when concealing 150,000 bits in the Lena image, the averages of the Normalized Cross-Correlation (NCC) and Mean-Squared Error (MSE) of our proposed method were 0.9952 and 37.9460, respectively, which were the highest. The sufficient experiments confirmed that the performance of the proposed method is satisfactory in terms of image embedding capacity and quality.
HBF-DH: An Enhanced Payload Hybrid Data Hiding Method Based on a Hybrid Strategy and Block Features
