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<p>Reversible Data Hiding (RDH) based on Pixel Value Ordering (PVO) has recently garnered significant attention from researchers. However, existing approaches face challenges related to the large size of the location map (LM) and limited embedding capacity (EC). To address these issues, this paper proposes an adaptive RDH approach that employs optimized low (L) and high (H) threshold estimation to minimize the size of the LM or eliminate its use entirely. By enabling the embedding phase to utilize multiple parameter values, EC is significantly enhanced. Additionally, the employed parameters act as a security key for extracting message bits and recovering an original image. Without knowledge of these parameters, the hidden message bits cannot be extracted, nor can the original image be successfully restored. Experimental results demonstrate that the proposed scheme outperforms existing PVO-based RDH methods in terms of EC, image visual quality, and resistance against extraction attacks.</p>

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An Novel Adaptive PVO-Based Reversible Data Hiding Method Using Optimized Low and High Threshold Estimation For Gray Images

  • 期刊论文

  • 发表日期：

    2025年8月13日

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  • Tuan Duc Nguyen,
  • Tinh Thanh Dao

摘要

Reversible Data Hiding (RDH) based on Pixel Value Ordering (PVO) has recently garnered significant attention from researchers. However, existing approaches face challenges related to the large size of the location map (LM) and limited embedding capacity (EC). To address these issues, this paper proposes an adaptive RDH approach that employs optimized low (L) and high (H) threshold estimation to minimize the size of the LM or eliminate its use entirely. By enabling the embedding phase to utilize multiple parameter values, EC is significantly enhanced. Additionally, the employed parameters act as a security key for extracting message bits and recovering an original image. Without knowledge of these parameters, the hidden message bits cannot be extracted, nor can the original image be successfully restored. Experimental results demonstrate that the proposed scheme outperforms existing PVO-based RDH methods in terms of EC, image visual quality, and resistance against extraction attacks.