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March 7, 2026SensorsOpen Access

APVCPC: An Adaptive Predicted Value Computation and Pixel Classification Framework for Reversible Data Hiding in Encrypted Images

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Authors

YWYaomin WangWHWenguang HeGXGangqiang Xiong

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Overview

APVCPC enhances embedding capacity and security in reversible data hiding for encrypted images, suggesting significant improvements over conventional methods.

Key Points

  • The aim is to improve reversible data hiding in encrypted images by optimizing embedding capacity and fidelity through a new framework.
  • Developed a context-aware prediction engine for adaptive estimation function selection based on texture complexity.
  • Introduced a dynamic threshold for pixel classification into loadable and non-loadable sets.
  • Utilized experimental validation on standard benchmarks and BOW-2 database for performance evaluation.
  • Achieved an average embedding rate exceeding 2.0 bits per pixel (bpp).
  • Ensured perfect reversibility of data extraction and image decryption.
  • Outperformed existing techniques in terms of both capacity and security metrics.

Cite This Study

Wang et al. (2026) studied this question.

synapsesocial.com/papers/69abc2725af8044f7a4ec063https://doi.org/10.3390/s26051636
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  1. 12-D Compressive Sensing-Based Visually Secure Multilevel Image Encryption Scheme2023 · 16 citations
  2. 2A Novel High-Capacity Reversible Data Hiding Scheme for Encrypted JPEG Bitstreams2018 · 75 citations
  3. 3Reversible Data Hiding in Encrypted Images With Secret Sharing and Hybrid Coding2023 · 80 citations