Using Bias Optimization for Reversible Data Hiding Using Image Interpolation
This is an incremental improvement for data hiding in image processing, addressing embedding capacity in compressed grayscale images.
The paper tackles reversible data hiding in compressed grayscale images by embedding secret bits into a compressed thumbnail using a novel interpolation method and Neighbour Mean Interpolation, resulting in significantly improved embedding capacities compared to the approach by Jung and Yoo.
In this paper, we propose a reversible data hiding method in the spatial domain for compressed grayscale images. The proposed method embeds secret bits into a compressed thumbnail of the original image by using a novel interpolation method and the Neighbour Mean Interpolation (NMI) technique as scaling up to the original image occurs. Experimental results presented in this paper show that the proposed method has significantly improved embedding capacities over the approach proposed by Jung and Yoo.