Title
Adaptive encoding based lossless data hiding method for VQ compressed images using tabu search
Abstract
A novel joint image coding and reversible data hiding method for vector quantization (VQ) compressed images is proposed in this paper. Since the original VQ indices often exhibit uncorrelated, a rearrangement of them by considering their correlations may benefit the prediction performance so as to reduce the required bitrate. In this study, the tabu search algorithm is employed to rearrange codewords by fully exploiting their neighboring correlations, yielding a moepressible rearranged indices. By combining more highly-correlated indices of a to-be-predicted index into prediction, the improved linear regression method is then applied to achieve a sharper prediction-error histogram and less required additional information. After prediction, an adaptive run-length encoding method is presented to encode prediction errors, thereby eliminating unnecessary indicators. Experimental results demonstrate that the proposed method effectively reduces the bitrate of the compressed image while providing a comparable hiding capacity.
Year
DOI
Venue
2022
10.1016/j.ins.2022.04.011
Information Sciences
Keywords
DocType
Volume
Vector quantization,Reversible data hiding,Index rearrangement,Tabu search algorithm,Linear regression method
Journal
602
ISSN
Citations 
PageRank 
0020-0255
0
0.34
References 
Authors
0
5
Name
Order
Citations
PageRank
Tiancong Zhang141.73
Shaowei Weng242.74
Zhijie Wu300.34
Juan Lin421.71
Wien Hong561830.63