High capacity steganographic algorithm based on payload adaptation and optimization

Abstract

The paper introduces a new and enhanced high capacity steganographic algorithm based on the original smart LSB pixel mapping and data rearrangement design. Throughout our research we've discovered that the best solutions for payload adaptation to the carrier image in our initial algorithms were found within the first 30 attempts, of which less than 4 have been improved during the evaluation and optimization stage. All others became redundant after a certain number of initial breeds (embedding solutions) have been generated. In this paper we introduce a more complex solution generator and evaluator that joins the iterative stages of the previous design for the purpose of optimizing and identifying the best solution in an earlier evaluation stage, while featuring an extended validation region than the original design. By focusing on reducing the image degradation in the embedding process with the original luminosity of the image as a quality metric, the algorithm is capable of maintaining even more of the original color quality. As outlined in the experimental results, this innovative new approach raises the logical visual and statistical imperceptibility of the resulting image therefore building an even stronger steganographic model.