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Adaptive Complexity for Pixel-Value-Ordering Based Reversible Data Hiding
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DOI：10.1109/LSP.2020.2996507.png)
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Abstract
En 中文
Pixel-value-ordering (PVO) is a widely used reversible data hiding (RDH) framework which aims to achieve the high quality of stego-image under low capacity. In this letter, we propose a general location-based adaptive complexity for PVO. Different from the block-based complexity in the previous PVO-based methods, our proposed method adaptively selects context pixels from the perspective of the relative locations of predicted pixel and prediction pixel. Consequently, different number of high correlation context pixels can be adaptively selected and the context pixels can break the limitation of the current block. Moreover, instead of sharing the same block complexity by two predicted pixels in the current block, each predicted pixel can be utilized independently according to its own corresponding complexity. Our proposed adaptive complexity can combine with any PVO-based methods and the experimental results show that our proposed method achieves a significant improvement in prediction accuracy and embedding performance.
Keywords:
Complexity theory
Correlation
Distortion
Interference
Media
Sorting
Fans
Reversible data hiding
pixel-value-ordering
predicted pixels
prediction pixels
context pixels
adaptive complexity
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