Reversible data hiding techniques with high message embedding capacity in images.

Area of Science:

• Computer Science
• Information Security
• Digital Image Processing

Background:

• Reversible Data Hiding (RDH) techniques embed data in images, allowing perfect restoration of the original.
• Early RDH methods used Image Histogram Modification; recent methods leverage Difference Image Histogram Modification for increased capacity.
• Neighboring pixels' correlation is exploited in difference-based methods, creating more space for embedded data.

Purpose of the Study:

• To propose a framework that increases the embedding capacity of reversible data hiding techniques.
• To enhance difference-based RDH methods by improving image regions suitable for data embedding.
• To achieve higher embedding capacity and better visual quality in marked images.

Main Methods:

• A novel framework is proposed that rearranges image columns or rows to enhance smooth regions.
• This rearrangement prepares the image for difference-based data embedding techniques.
• The method is applied to various image types, including textures and patterns.

Main Results:

• The proposed method increases message embedding capacity by over 50% compared to existing techniques.
• Marked images exhibit superior visual quality compared to state-of-the-art RDH methods.
• The technique is undetectable by Pixel Difference Histogram (PDH) Stegoanalysis.

Conclusions:

• The proposed framework significantly boosts embedding capacity and visual quality for reversible data hiding.
• Image data rearrangement is an effective strategy to improve difference-based RDH techniques.
• The method offers a robust and secure solution for invisible data embedding.