High capacity reversible data hiding with interpolation and adaptive embedding.

Area of Science:

• Computer Science
• Information Security
• Digital Forensics

Background:

• Existing reversible data hiding schemes struggle with varying embedding capacity needs across applications like digital images, video, and big data.
• Current methods often compromise rate-distortion performance when handling variable-sized payloads.

Purpose of the Study:

• To develop a novel Interpolation-based Reversible Data Hiding (IRDH) scheme with adaptive embedding capacity.
• To improve rate-distortion performance for diverse data types and payload sizes.

Main Methods:

• Formulated a capacity control parameter for adaptive embedding, determining embeddable bits per pixel.
• Utilized logical (bit-wise) correlation between embeddable and estimated embedded pixels.
• Computational modeling and evaluation using popular test images.

Main Results:

• The proposed adaptive IRDH scheme successfully meets varying capacity requirements within a defined range.
• Achieved better embedded image quality compared to existing IRDH schemes.
• Demonstrated significantly improved embedding rate-distortion performance in experimental evaluations.

Conclusions:

• The novel adaptive IRDH scheme offers a flexible and efficient solution for reversible data hiding.
• It provides superior rate-distortion performance, especially for applications with fluctuating data embedding needs.
• This advancement is crucial for secure and efficient data management in multimedia, big data, and biological data applications.