JOURNAL ARTICLE

High capacity lossless data hiding based on integer wavelet transform

Abstract

This paper proposes a novel approach to high capacity lossless data hiding based on integer wavelet transform, which embeds high capacity data into the most insensitive bit-planes of wavelet coefficients. Specifically, three high capacity lossless data hiding methods, namely A, B and C are proposed. Method A is the traditional lossless data hiding technique, which can losslessly recover the original image. The capacity can reach 1/10 of the data volume that the original image occupies and histogram modification is used to prevent over/underflow. Method B is not a traditional lossless data hiding technique. It can only losslessly recover the pre-processed image instead of the original image. However, the capacity can reach 1/2 of the data volume that the original image occupies. It has better visual quality than replacing the four least significant bit-planes in the spatial domain. Method C has not only the larger capacity but also better visual quality than Method B. However, it can only losslessly recover the hidden data. These three methods passed through the test on all 1096 images of CorelDraw database. These techniques can be applied to e-government, e-business, e-medical data systems, e-law enforcement and military systems.

Keywords:
Lossless compression Arithmetic underflow Computer science Information hiding Wavelet transform Image (mathematics) Artificial intelligence Histogram Image quality Wavelet Computer vision Algorithm Data compression

Metrics

38
Cited By
2.56
FWCI (Field Weighted Citation Impact)
2
Refs
0.90
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Advanced Steganography and Watermarking Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Digital Media Forensic Detection
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Chaos-based Image/Signal Encryption
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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