Description: 数字图像处理的考试试卷，很好的东西，我考试时就是用了它。-Digital image processing of examination papers, a very good thing, I exam is to use it. Platform: |
Size: 188416 |
Author:郭龙 |
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Description: 小波变换在数字图像处理中的应用是小波变换典型的应用之一。由信号分析中傅里叶变换的不足引出小波变换, 然后简单介绍了小波变换的定义和种类, 分析了小波变换的性质和Mallat 算法, 总结了小波变换在数字图像处理中的四种应用:基于小波变换的图像压缩、图像去噪、图像增强和图像融合, 分析了四种应用的过程及特点, 同时进行了相应的Matlab试验与仿真。试验结果表明, 小波变换在数字图像处理中的应用切实可行、简单方便、效果好、有很强的实用价值, 有较好的应用前景。-The applicatio n of wave let transform in digital imag e processing is one o f the ty pical applications of wavelet transform .The w avelet transform is introduced fo r the lack o f Fourier tr ansfo rm in the sig nal analysis , the definitio n and types of the wavelet transform ar e pro po sed briefly , and its proper ties and Mallat alg orithm a re analy zed .Fo ur kinds o f applicationsof wavelet transfo rm in dig ita l image pro ce ssing ar e summarized(imag e compr essio n, image denoising , image enhancement and image fusion based o n w avele t tr ansfo rm), the processe s and char acte ristics of this fo ur kinds of applicatio ns are analyzed,meanw hile the co r respo nding Ma tlab ex pe riment and simulatio n ar e made .Ex perimental results show that it is practical, simple , convenient a nd effective , and has a stro ng practical value and a g oo d applicatio n pro spects for the wavele t transform in digital image pro cessing . Platform: |
Size: 506880 |
Author:kiel |
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Description: Similar to other digital assets, deep neural network
(DNN) models could suffer from piracy threat initiated by insider
and/or outsider adversaries due to their inherent commercial
value. DNN watermarking is a promising technique to mitigate
this threat to intellectual property. This work focuses on black-
box DNN watermarking, with which an owner can only verify
his ownership by issuing special trigger queries to a remote
suspicious model. However, informed attackers, who are aware
of the watermark and somehow obtain the triggers, could
forge fake triggers to claim their ownerships since the poor
robustness of triggers and the lack of correlation between the
model and the owner identity. This consideration calls for new
watermarking methods that can achieve better trade-off for
addressing the discrepancy. In this paper, we exploit frequency
domain image watermarking to generate triggers and build our
DNN watermarking algorithm accordingly. Since watermarking
in the frequency domain is high concealment and robust to
signal processing operation, the proposed algorithm is superior to
existing schemes in resisting fraudulent claim attack. Besides, ex-
tensive experimental results on 3 datasets and 8 neural networks
demonstrate that the proposed DNN watermarking algorithm
achieves similar performance on functionality metrics and better
performance on security metrics when compared with existing
algorithms. Platform: |
Size: 374457 |
Author:bamzi334 |
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