一种新的基于心理视觉模型的盲彩色水印。

IF 2.3 4区 医学 Q1 Neuroscience
Pascal Lefevre, David Alleysson, Philippe Carre
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引用次数: 0

摘要

在本文中,我们解决了使用人类视觉系统(HVS)模型来提高水印不可见性的问题。提出了一种基于色差感知最小化的彩色水印算法。该算法基于视锥光感受器动态的心理视觉模型。我们使用这个模型来确定人类对特定颜色的辨别能力,从而确定修改颜色像素的最佳策略。结果表明,彩色版的点阵量化指数调制(LQIM)方法在心理视觉不可见性和对多种图像畸变的鲁棒性方面有所改善。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

A new blind color watermarking based on a psychovisual model.

A new blind color watermarking based on a psychovisual model.

A new blind color watermarking based on a psychovisual model.

A new blind color watermarking based on a psychovisual model.

In this paper, we address the problem of the use of a human visual system (HVS) model to improve watermark invisibility. We propose a new color watermarking algorithm based on the minimization of the perception of color differences. This algorithm is based on a psychovisual model of the dynamics of cone photoreceptors. We used this model to determine the discrimination power of the human for a particular color and thus the best strategy to modify color pixels. Results were obtained on a color version of the lattice quantization index modulation (LQIM) method and showed improvements on psychovisual invisibility and robustness against several image distortions.

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来源期刊
Journal of Mathematical Neuroscience
Journal of Mathematical Neuroscience Neuroscience-Neuroscience (miscellaneous)
自引率
0.00%
发文量
0
审稿时长
13 weeks
期刊介绍: The Journal of Mathematical Neuroscience (JMN) publishes research articles on the mathematical modeling and analysis of all areas of neuroscience, i.e., the study of the nervous system and its dysfunctions. The focus is on using mathematics as the primary tool for elucidating the fundamental mechanisms responsible for experimentally observed behaviours in neuroscience at all relevant scales, from the molecular world to that of cognition. The aim is to publish work that uses advanced mathematical techniques to illuminate these questions. It publishes full length original papers, rapid communications and review articles. Papers that combine theoretical results supported by convincing numerical experiments are especially encouraged. Papers that introduce and help develop those new pieces of mathematical theory which are likely to be relevant to future studies of the nervous system in general and the human brain in particular are also welcome.
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