.png){kind=icon}
返回
A Spatial Image Steganography Method Based on Nonnegative Matrix Factorization
.png){kind=icon}
PRE
AI
DOI：10.1109/LSP.2018.2856630.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Research on adaptive steganography mainly focuses on how to design a reasonable cost function and how to utilize that cost function to achieve embedding in a stegoimage with the minimal distortion based on syndrome-trellis codes. Because previous adaptive steganographic methods use convolution with filters to obtain the residuals, these methods do not make good use of the textures of the image itself in the design of the cost function. In this letter, we define a new cost function that uses nonnegative matrix factorization to predict the image pixels and utilizes the mutual dependencies among the pixels to calculate the costs. We present a novel cost function in which the residuals are not calculated via convolution with constant filters. Experimental results show that our method outperforms the state-of-the-art MiPOD, spatial universal wavelet relative distortion, wavelet obtained weights, and HUGO-BD methods in resisting steganalysis based on the spatial rich model and is slightly superior to the high-pass, low-pass, low-pass method.
Keyword:
Adaptive steganography
no constant template
nonnegative matrix factorization (NMF)
pixelwise mutual prediction
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
9.6
论文数:
1.1W
被引数:
1.7W
机构
引用论文
4-1BB Signaling Activates the T Cell Factor 1 Effector/β-Catenin Pathway with Delayed Kinetics via ERK Signaling and Delayed PI3K/AKT Activation to Promote the Proliferation of CD8+ T Cells.png)
PLoS ONE
OAAI
PLoS ONEIF0
OAAI分享收藏Assessing toxicity mechanism of silver nanoparticles by using brine shrimp (Artemia salina) as modelChemosphere
ChemosphereIF0
PREAI
分享收藏分享收藏
查看更多内容