Wavelet-based Image Steganography using the Idea of Embedding in Areas of High Frequency Subbands with Large Variations

Steganography is the science and art of hiding the existence of communication. In steganography, by hiding information in a digital media, the existence of communication remains hidden from the enemy’s view. The idea of spatial-based adaptive methods is to embed more in the edge areas of the image. In these methods, areas of the image that have more changes are prioritized for embedding. On the other hand, wavelet-based methods perform embedding in high frequency subbands to match the human vision system. The proposed idea in this paper is embedding with higher priority in areas of high frequency subbands resulting from wavelet transform that have many changes. First, according to the length of the data, a threshold value is determined, based on which suitable embedding areas are identified in each high frequency subband, and then the embedding process is performed in them. This process is such that the receiver can extract the data completely by repeating it. The implementation results show that in the proposed method, the use of Integer Wavelet Transform (IWT) is more successful than Discrete Wavelet Transform (DWT). The quality of the resulted stego image is higher and its security is more than the other wavelet-based methods.