Hybrid Predictor and Field-Biased Context Pixel Selection Based on PPVO

作者：Xiang, Hongyin^*; Yuan, Jinsha; Hou, Sizu

来源：Mathematical Problems in Engineering, 2016, 2016: 2585983.

DOI：10.1155/2016/2585983

• REVERSIBLE IMAGE WATERMARKING
• EXPANSION

Most pixel-value-ordering (PVO) predictors generated prediction-errors including -1 and 1 in a block-by-block manner. Pixel-based PVO (PPVO) method provided a novel pixel scan strategy in a pixel-by-pixel way. Prediction-error bin 0 is expanded for embedding with the help of equalizing context pixels for prediction. In this paper, a PPVO-based hybrid predictor (HPPVO) is proposed as an extension. HPPVO predicts pixel in both positive and negative orientations. Assisted by expansion bins selection technique, this hybrid predictor presents an optimized prediction-error expansion strategy including bin 0. Furthermore, a novel field-biased context pixel selection is already developed, with which detailed correlations of around pixels are better exploited more than equalizing scheme merely. Experiment results show that the proposed HPPVO improves embedding capacity and enhances marked image fidelity. It also outperforms some other state-of-the-art methods of reversible data hiding, especially for moderate and large payloads.

• 出版日期2016
• 单位华北电力大学