Novel Integer Reversible Charlier Transform for Image Reversible Data Hiding Application

Abstract

The discrete Charlier moment transform, while extensively utilized in image processing, is inherently lossy and non-integer reversible, making it unsuitable for lossless image applications. To address this, we propose the Integer Reversible Charlier Transform (IRCT), which operates on integer values and produces integer coefficients, enabling perfect and unique recovery of the original input data. The IRCT maintains the orthogonality and invertibility ensuring exact similarity between original and reconstructed images. We leverage the capabilities of the IRCT to develop a novel reversible data hiding (RDH) scheme. This scheme embeds additional data into images by modifying the histogram in the IRCT domain. By capitalizing on the concentrated nature of the IRCT histogram, characterized by high peaks, our method achieves a significantly high embedding capacity while preserving image quality and robustness to statistical attacks. Comparative performance evaluations underscore the effectiveness of the IRCT-based RDH scheme over existing techniques across various domains, positioning it as a promising solution for secure data transmission.