CVMMFeb 12, 2022

Reversible data hiding with dual pixel-value-ordering and1minimum prediction error expansion

arXiv:2202.08100v110 citations
Originality Incremental advance
AI Analysis

This is an incremental improvement for reversible data hiding in image processing, enhancing fidelity and capacity.

The paper tackles the problem of improving rate-distortion performance in reversible data hiding by introducing a dual-PVO scheme with prediction error expansion, resulting in better embedded image quality and higher embedding rates compared to state-of-the-art methods.

Pixel Value Ordering (PVO) holds an impressive property for high fidelity Reversible Data Hiding (RDH). In this paper, we introduce a dual-PVO (dPVO) for Prediction Error Expansion(PEE), and thereby develop a new RDH scheme to offer a better rate-distortion performance. Particularly, we propose to embed in two phases: forward and backward. In the forward phase, PVO with classic PEE is applied to every non-overlapping image block of size 1x3. In the backward phase,minimum-set and maximum-set of pixels are determined from the pixels predicted in the forward phase. The minimum set only contains the lowest predicted pixels and the maximum set contains the largest predicted pixels of each image block. Proposed dPVO withPEE is then applied to both sets, so that the pixel values of the minimum set are increased and that of the maximum set are decreased by a unit value. Thereby, the pixels predicted in the forward embedding can partially be restored to their original values resulting in both better-embedded image quality and a higher embedding rate. Experimental results have recorded a promising rate-distortion performance of our scheme with a significant improvement of embedded image quality at higher embedding rates compared to the popular and state-of-the-art PVO-based RDHschemes.

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