An adaptive image steganography method based on integer wavelet transform using genetic algorithm

Abstract

Steganography is the science and art of concealing the existence of communication. The idea proposed in this paper is that the coefficients of the high-frequency subbands are more suitable for embedding, as they are surrounded by larger coefficients and represent the image's edge areas. In this method, the appropriate embedding coefficients are selected using an edge intensity criterion based on a local neighborhood analysis. The proposed method begins by blocking the image and then applying a wavelet transform to each block. Several coefficients in each high-frequency subband are identified, and then, using a genetic algorithm, the coefficients are selected so that the generated stego image has the highest PSNR value. The proposed method is more successful when the Integer Wavelet Transform (IWT) is used rather than the Discrete Wavelet Transform (DWT). The proposed method produces a higher-quality stego image than existing methods, and it is secure against steganalysis attacks.