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Robust and High Capacity Image Watermarking Based on Jointly Coding and Embedding Optimization

机译:基于联合编码和嵌入优化的鲁棒大容量图像水印

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摘要

A new informed image watermarking algorithm is presented in this paper, which can achieve the information rate of 1/64 bits/pixel with high robustness. Firstly, the LOT (Locally Optimum Test) detector based on HMM in wavelet domain is developed to tackle the issue that the exact strength for informed embedding is unknown to the receiver. Then based on the LOT detector, the dirty-paper code for informed coding is constructed and the metric for the robustness is defined accordingly. Unlike the previous approaches of informed watermarking which take the informed coding and embedding process separately, the proposed algorithm implements a jointly coding and embedding optimization for high capacity and robust watermarking. The Genetic Algorithm (GA) is employed to optimize the robustness and distortion constraints simultaneously. Extensive simulations are carried out which demonstrates that the proposed algorithm achieves significant improvements in performance against JPEG, gain attack, low-pass filtering and so on.
机译:提出了一种新的信息图像水印算法,该算法可以达到1/64位/像素的信息速率,并且具有较高的鲁棒性。首先,开发了基于小波域HMM的LOT(局部最优测试)检测器,以解决接收器未知用于知情嵌入的确切强度的问题。然后,基于LOT检测器,构造用于知情编码的脏纸代码,并相应地定义鲁棒性的度量。与以前的将有信息的编码和嵌入过程分开进行的有信息的水印方法不同,该算法实现了针对大容量和鲁棒性水印的联合编码和嵌入优化。遗传算法(GA)用于同时优化鲁棒性和失真约束。进行了广泛的仿真,结果表明所提出的算法在针对JPEG,增益攻击,低通滤波等方面的性能方面取得了显着提高。

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