作者: Linlin Zhang , Jianjun Wang
DOI: 10.1007/978-3-642-53778-3_48
关键词:
摘要: Steganography in sparse domain has drawn more and attention the past few years due to its high security. In this paper, we propose a steganography based on morphological component for grayscale images. Images are composed of two components—piecewise smooth (cartoon-like) parts textures. Complex contents images harder be modeled, such as textures, thus cannot easily detected when embed secret data them. By properly select dictionaries, content-adaptive can have rather large payloads low statistical detectability. We combine dictionaries obtain coefficients components an image, separately. When embedding domain, give top priority present ways construct these kinds our work, using mathematical models well wisely learned by K-SVD algorithm. Experiments show better visual quality stego-images undetectability messages comparison with other methods domain.