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Efficient capacity-distortion reversible data hiding based on combining multipeak embedding with local complexity
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AI
DOI：10.1007/s10489-022-03323-8.png)
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Abstract
En 中文
Recently, most histogram shifting-based reversible data hiding (RDH) algorithms have considered the impact of textural information on embedding performance, while exploiting pixels with different local complexities. Prioritizing pixels with small local complexities to accommodate secret data decreases the invalid shifting pixels, thereby reducing distortion. However, though effective, the local complexity is not calculated precisely enough, which results in inaccurate texture division and does not considerably reduce distortion. Thus, we employ a novel local complexity calculation and multipeak embedding (MPE) to effectively improve the capacity-distortion performance. Specifically, the host image is first preprocessed by the dot-cross pattern and divided into two subsets. Then the pixel local complexity of each subset is computed by using the spatial correlation of pixels (SCOP) to improve calculation accuracy. Finally, the peak bins to be expanded in the regions with lower local complexity are adaptively selected for embedding with secret data by MPE. To ensure that the authorized operator can securely gain error-free secret data, we design the location index sequences as special keys, which guarantee the algorithm reversibility and enhance the security of the algorithm at the same time. Experimental results show that our algorithm has superior embedding effectiveness compared to some state-of-the-art RDH methods.
Keywords:
Reversible data hiding
Invalid shifting pixels
Local complexity
Location index mechanism
Multipeak embedding