Using Bias Optimization for Reversible Data Hiding Using Image Interpolation

TL;DR

This paper introduces a reversible data hiding technique for compressed grayscale images that leverages a novel interpolation method and neighbor mean interpolation to enhance embedding capacity while maintaining image quality.

Contribution

It presents a new reversible data hiding approach using bias optimization and image interpolation techniques, improving embedding capacity over existing methods.

Findings

Significantly improved embedding capacity compared to prior methods.

Effective use of neighbor mean interpolation for reversible data hiding.

Maintains image quality while embedding secret data.

Abstract

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.