关键词: 自嵌入, 自恢复, 信息隐藏, 显著性

Abstract:  The purpose of image self-embedding is to achieve content authentication and self-recovery by imperceptibly embedding relevant information into the host image. This paper proposes a novel self-embedding method based on significance classification. After classifying the image into three kinds of regions dynamically, the code length and embedding capacity of each block are determined. Using fountain coding, the reference information is embedded into the entire image. The proposed method is superior to the traditional methods in two aspects. First, the method assigns different code length to different regions so that the recovery quality for the whole image is good and significant regions can be protected effectively. Second, the method embeds different amounts of data into different regions thus avoiding false contour and ensuring good quality of the stego-image.

Key words: self-embedding, self-recovery, data hiding, significant region