Reversible data hiding algorithm based on unidirectional extremum prediction error expansion

DOI:	10.11809/bqzbgcxb2023.09.042
Keywords:	reversible data hiding; local complexity; unidirectional error expansion; extreme value prediction; asymmetric histogram
Abstract:	In order to solve the problems of high distortion and low embedding in existing reversible data hiding algorithms effectively, a new reversible data hiding (RDH) algorithm based on unidirectional error expansion is proposed. The algorithm adopts a pixel rhombus prediction strategy and uses four reference pixels on the cross neighborhood of the target pixel to calculate its prediction error value. In addition, the algorithm predicts its difference by the prediction error value of the neighboring reference pixels and uses the redundancy of the two to calculate two extreme value predictors and generate the corresponding asymmetric histogram. Moreover, the algorithm calculates the local complexity value of each target pixel according to the value of the prediction error. Then, the local complexity value of each target pixel is calculated, and the prediction error is ranked according to the value so that the pixels with low complexity are prioritized. Finally, the watermark information is divided into two rounds for adaptive embedding in turn through the unidirectional prediction error expansion of the histogram. The experimental results show that the algorithm can effectively reduce image distortion and has a high embedding capacity, which has certain performance advantages compared with similar reversible information hiding algorithms.
Issue:	Vol. 44 No. 9 (2023)
Published:	2023-09-28
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