Image steganography is a common form of information hiding which embeds as many message bits into images and keep the introduced distortion imperceptible. How to balance the trade-off between the capacity and imperceptibility has become a very important issue in the researches of steganography. In this chapter, we discuss one kind of the solution for disposing the trade-off, named adaptive image steganography. After a brief review, we present two methods based on structural similarity metric. The first one is based on the generalized LSB, in which the substitution depth vector is obtained via the dynamic programming under the constraint of an allowable distortion. The second method is proposed to use adaptive quantization-embedder to carry message bits. Different from the first method, the distortion index is constructed by contrast-correlation distortion. The other difference is that the parameters of the adaptive quantization embedder are embedded into the image containing message bits by the reversible da a hiding method. Beside that, we also bring forward some attractive directions worthy of being studied in the future. Furthermore, we find that the existing methods do not have a good way to control the amount of information and the distortion as an extract manner, and most schemes are designed just according to the experiences and experiments.
Towards a Point Cloud Structural Similarity Metric
