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基于多尺度滤波器的空域图像隐写增强算法

吴俊锜, 翟黎明, 王丽娜, 方灿铭, 吴畑

吴俊锜, 翟黎明, 王丽娜, 方灿铭, 吴畑. 基于多尺度滤波器的空域图像隐写增强算法[J]. 计算机研究与发展, 2020, 57(11): 2251-2259. DOI: 10.7544/issn1000-1239.2020.20200441
引用本文: 吴俊锜, 翟黎明, 王丽娜, 方灿铭, 吴畑. 基于多尺度滤波器的空域图像隐写增强算法[J]. 计算机研究与发展, 2020, 57(11): 2251-2259. DOI: 10.7544/issn1000-1239.2020.20200441
Wu Junqi, Zhai Liming, Wang Lina, Fang Canming, Wu Tian. Enhancing Spatial Steganographic Algorithm Based on Multi-Scale Filters[J]. Journal of Computer Research and Development, 2020, 57(11): 2251-2259. DOI: 10.7544/issn1000-1239.2020.20200441
Citation: Wu Junqi, Zhai Liming, Wang Lina, Fang Canming, Wu Tian. Enhancing Spatial Steganographic Algorithm Based on Multi-Scale Filters[J]. Journal of Computer Research and Development, 2020, 57(11): 2251-2259. DOI: 10.7544/issn1000-1239.2020.20200441
吴俊锜, 翟黎明, 王丽娜, 方灿铭, 吴畑. 基于多尺度滤波器的空域图像隐写增强算法[J]. 计算机研究与发展, 2020, 57(11): 2251-2259. CSTR: 32373.14.issn1000-1239.2020.20200441
引用本文: 吴俊锜, 翟黎明, 王丽娜, 方灿铭, 吴畑. 基于多尺度滤波器的空域图像隐写增强算法[J]. 计算机研究与发展, 2020, 57(11): 2251-2259. CSTR: 32373.14.issn1000-1239.2020.20200441
Wu Junqi, Zhai Liming, Wang Lina, Fang Canming, Wu Tian. Enhancing Spatial Steganographic Algorithm Based on Multi-Scale Filters[J]. Journal of Computer Research and Development, 2020, 57(11): 2251-2259. CSTR: 32373.14.issn1000-1239.2020.20200441
Citation: Wu Junqi, Zhai Liming, Wang Lina, Fang Canming, Wu Tian. Enhancing Spatial Steganographic Algorithm Based on Multi-Scale Filters[J]. Journal of Computer Research and Development, 2020, 57(11): 2251-2259. CSTR: 32373.14.issn1000-1239.2020.20200441

基于多尺度滤波器的空域图像隐写增强算法

基金项目: 国家自然科学基金重点项目(U1536204);国家自然科学基金项目(U1836112,61876134)
详细信息
  • 中图分类号: TP309

Enhancing Spatial Steganographic Algorithm Based on Multi-Scale Filters

Funds: This work was supported by the Key Program of the National Natural Science Foundation of China (U1536204) and the National Natural Science Foundation of China (U1836112, 61876134).
  • 摘要: 隐写是一种利用图像、视频、音频等多媒体载体实现隐蔽传输的技术.如何在尽可能减少对载体影响的情况下嵌入尽可能多的信息一直是隐写算法的研究重点.随着双层校验格码(syndrome tellis codes, STC)的引入,隐写算法的嵌入效率能够达到理论上界.因此,隐写算法的设计重心变为了设计用于衡量图像像素嵌入安全性的失真函数.失真函数是自适应隐写算法的核心.对于空域图像隐写而言,失真函数通常是基于图像的复杂性原则,即载体图像中的纹理区域通常具有较低的失真代价,而平坦区域通常具有更高的失真代价.然而,基于图像内容的多样性,这种准则并不能适用于一幅图像中的所有像素点.提出了一种适用于空域隐写算法的隐写增强算法,通过多尺度滤波器对载体图像进行增强,使得在增强不同尺度的纹理区域的同时减少对图像平坦区域的增强.增强后的失真代价遵循了复杂性原则,并解决了失真代价分配不当的问题.实验结果表明:所提出的算法能够适用于现有的空域隐写算法,并且能够提升它们的抗隐写分析检测能力.
    Abstract: Steganography is a kind of convert communication technique which uses multimedia carriers such as images, videos, and audios. How to embed secret messages as much as possible under the condition of minimizing the impact on the carrier is always the research focus of steganographic algorithms. After the introduction of STC (syndrome trellis codes), the embedding efficiency of steganographic algorithms can approach the theoretical upper bound. Therefore, the design of steganographic algorithms focuses on the distortion functions which are designed to measure the embedding security of image pixels. Distortion functions are crucial to content-adaptive steganography. For spatial image steganography, the distortion functions are always designed with a texture-complexity criterion of images, where textured regions are assigned low embedding costs and flat regions are assigned high embedding costs. However, for the variety of image contents, this criterion may not be sufficiently satisfied for all pixels in a given image. In this paper, we propose an enhancing spatial steganographic algorithm to refine the embedding costs by using multi-scale filters, which can better enhance texture regions in different scales while reducing the enhancement of smooth regions. The refined embedding costs adequately conform to the above criterion, and thus overcome the problem of improper cost assignment. Experimental results demonstrate that the proposed algorithm can be applied to existing spatial image steganographic algorithms, and can also improve their steganographic security against image steganalysis.
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出版历程
  • 发布日期:  2020-10-31

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