基于图像纹理的自适应鲁棒水印算法

Xing Yang, Y. Liu, Tingge Zhu
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引用次数: 0

摘要

数字水印是解决版权保护和内容认证的关键技术。现有的大多数水印算法都是基于全局嵌入的,不能很好地平衡水印的不可感知性和鲁棒性。本文提出了一种基于图像纹理的自适应鲁棒水印算法,主要包括:(1)将彩色图像从RGB空间转换到Lab空间,并基于L分量提取稳定尺度不变特征变换(SIFT)点作为水印的嵌入位置;(2)利用机器学习提取结构化森林边缘作为水印图像,利用提升小波变换(LWT)对水印图像进行分解,然后利用逻辑混沌变换对水印图像进行加密;(3)考虑到人的视觉系统,利用L分量的亮度信息和纹理复杂度自适应选择强度因子。实验结果表明,与其他相关算法相比,本文算法在Lab空间中具有更好的视觉不可见性和抗各种攻击的鲁棒性,特别是对裁剪、噪声和JPEG压缩攻击。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Adaptive Robust Watermarking Algorithm Based on Image Texture
Digital watermarking is a key technology to solve copyright protection and content authentication. Most existing watermarking algorithms are based on global embedding, which cannot well balance the imperceptibility and robustness of watermarking. This paper proposes an adaptive robust watermarking algorithm based on image texture, which mainly includes: (1) color image is converted from RGB space to Lab space and the stable scale invariant feature transform(SIFT) points are extracted based on L component as the embedding position of watermark; (2)the structured forest edge is extracted using machine learning as the watermark image which is decomposed by using lifting wavelet transform (LWT) and then encrypted using logical chaos transform; (3)in consideration of human visual system, the strength factor is adaptively selected by using the brightness information and texture complexity of the L component. Experimental results show that the proposed algorithm in Lab space has the better visual invisibility and robustness to resist various attacks, especially for cropping, noise and JPEG compression attacks in comparison with other related algorithms.
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