New Framework of Self-Embedding Fragile Watermarking Based on Reference Sharing Mechanism

2022 
We proposed in this paper a new self-embedding framework based on a reference sharing mechanism. The framework has high flexibility; it can not only estimate the optimal recovered image quality based on a given tampering rate but also estimate the largest tampering rate that the framework can resist based on the given peak signal-to-noise ratio (PSNR) of the recovered image. When the tampering rate is given, we first calculate the largest number of character bits and then allocate an appropriate number of character bits according to the complexity of the image block to achieve the optimal recovered image quality. When the PSNR of the recovered image is given, the number of character bits is minimized by satisfying the corresponding constraints to achieve the largest tolerable tampering rate. Experimental results show the flexibility, effectiveness, and superiority of the proposed scheme compared with some reported schemes.
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