| 摘要: |
| 先前众多的DWT(discrete wavelet transform)域水印算法几乎都是私有水印或易脆水印,而针对版权保护的鲁棒的、公开的小波域水印算法却极少.在充分考虑人类视觉系统掩蔽特性的基础上,首先给出基于图像分块的临界噪声阈值矩阵JND(just noticed difference),进而提出了一种基于DWT的鲁棒公开水印技术.算法首先把原图像各8(8块按Hilbert扫描顺序排列,然后在原图像分块的Hilbert序列中选取两相邻块分别进行一层DWT,再结合各分块JND阈值,通过不同强度地调整两相邻块各对应细节子带均值之间的大小关系以自适应地嵌入水印.嵌入水印具有很好的透明性,水印嵌入强度是与原图像特征相自适应的.同时,水印的提取无须求助于原图像.此外,实验结果也证明,该算法对常见图像处理操作、有损压缩和裁剪、挤压、像素移位等几何变换有较高的鲁棒性,特别是信号增强操作处理几乎不影响水印的正确提取,所以该算法是有效和实用的. |
| 关键词: 离散小波变换 公开水印技术 人类视觉系统 Hilbert扫描 |
| DOI： |
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| 基金项目:Supported by the National Grand Fundamental Research Program of Ministry of Education of China under Grant No.200139 (国家教育部科研重点项目); the Natural Science Foundation of Guizhou Province of China under Grant No.1993414 (贵州省自然科学基金) |
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| A Robust Image-Adaptive Public Watermarking Technique in Wavelet Domain |
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YANG Heng-Fu,CHEN Xiao-Wei
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| Abstract: |
| Most previous DWT-based watermarking algorithms belong to either private watermarking algorithms or fragile watermarking algorithms, but there are few DWT-based robust public watermarking techniques for copyright protection. By taking full advantage of the masking characteristics of the human visual system, first a JND (just noticed difference) threshold matrix based on block is given in this paper, and then a robust image-adaptive public watermarking technique operating in DWT domain is presented. Firstly, the 8? blocks of the original image are rearranged into a 1-D Hilbert sequence in Hilbert scanning order. Then two neighboring blocks are selected from the Hilbert sequence of the host image blocks in turn, and 1-level DWT is applied to the two chosen blocks. Finally, a corresponding detail subband is chose from three detail subbands of the two neighboring blocks at a time, respectively. A binary watermark with visually recognizable patterns is embedded into the host image by modifying the polarity of the average value of the two corresponding subbands. The embedded watermark is invisible to human eyes and adapted to the original image by exploiting the HVS masking characteristics. The experimental results show that the proposed algorithm is effective and robust to common image processing operations and some geometric distortions such as cropping, pinching, pixel-shift, and so on, especially, it receives better robustness under signal enhancement operations. So a conclusion can be made that the proposed technique is practical. |
| Key words: discrete wavelet transformation public watermarking technique human visual system Hilbert scanning |
