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http://hdl.handle.net/11375/25517
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DC Field | Value | Language |
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dc.contributor.advisor | Chen, Jun | - |
dc.contributor.author | Zhao, Wenjie | - |
dc.date.accessioned | 2020-07-08T15:23:46Z | - |
dc.date.available | 2020-07-08T15:23:46Z | - |
dc.date.issued | 2020 | - |
dc.identifier.uri | http://hdl.handle.net/11375/25517 | - |
dc.description.abstract | The digital image watermarking is a process that embeds a secrete sequence into a digital image or a video segment to protect its copyright information. There are several methods utilized to deal with the watermarking problem. There are in total two different kinds: the popular neural network and the traditional methods. And for the traditional methods, according to their working region, they can be divided into two groups: spatial domain-related algorithms (e.g., LSB SVD) and transformed domain algorithms (e.g., DCT, DWT). The spatial domain algorithms are the methods that directly work on the pixel values of the image, while the transformed domain algorithms are the methods that work on the rate of change of the image pixels. In the thesis, first of all, we are going to propose a modified hybrid the scheme, which has better results compared with the paper (Lin and Wan 2016). Then, we are going to offer a brand-new method concerning the LDPC-LDGM coding structure in the area of information theory to deal with the digital watermarking problem. Notice that this LDGM-LDPC nested code watermarking scheme only provides a particular case example, which is implemented by one of the teammates Dr. Mahdi, and there is still much space for improvement. However, according to the step tests in chapter 4.4, we have achieved a reasonably good result in imperceptibility and robustness. | en_US |
dc.language.iso | en | en_US |
dc.subject | Digital Watermarking | en_US |
dc.title | Digital Image Watermarking: Old and New | en_US |
dc.type | Thesis | en_US |
dc.contributor.department | Electrical and Computer Engineering | en_US |
dc.description.degreetype | Thesis | en_US |
dc.description.degree | Master of Applied Science (MASc) | en_US |
Appears in Collections: | Open Access Dissertations and Theses |
Files in This Item:
File | Description | Size | Format | |
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Zhao_Wenjie_202006_MASc.pdf | 2.27 MB | Adobe PDF | View/Open |
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