New Framework for Code-Mapping-based Reversible Data Hiding in JPEG Images

TL;DR

This paper introduces a new framework for reversible data hiding in JPEG images using code mapping, employing a genetic algorithm to optimize code mappings for high capacity and minimal file size increase.

Contribution

It proposes a novel code mapping strategy and a GA-based optimization method for improved reversible data hiding in JPEG images.

Findings

Achieves high embedding capacity without signal distortion.

Effectively suppresses file size expansion.

Demonstrates superior performance over existing methods.

Abstract

Code mapping (CM) is an efficient technique for reversible data hiding (RDH) in JPEG images, which embeds data by constructing a mapping relationship between the used and unused codes in the JPEG bitstream. This study presents a new framework for designing a CM-based RDH method. First, a new code mapping strategy is proposed to suppress file size expansion and improve applicability. Based on our proposed strategy, the mapped codes are redefined by creating a new Huffman table rather than selecting them from the unused codes in the original Huffman table. The critical issue of designing the CM-based RDH method, that is, constructing code mapping, is converted into a combinatorial optimization problem. This study proposes a novel CM-based RDH method that utilizes a genetic algorithm (GA). The experimental results demonstrate that the proposed method achieves a high embedding capacity with no signal distortion while suppressing file size expansion.