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A Novel STDM Watermarking Using Visual Saliency-Based JND Model
- Source :
- Information; Volume 8; Issue 3; Pages: 103, Information, Vol 8, Iss 3, p 103 (2017)
- Publication Year :
- 2017
- Publisher :
- Multidisciplinary Digital Publishing Institute, 2017.
-
Abstract
- The just noticeable distortion (JND) model plays an important role in measuring the visual visibility for spread transform dither modulation (STDM) watermarking. However, the existing JND model characterizes the suprathreshold distortions with an equal saliency level. Visual saliency (VS) has been widely studied by psychologists and computer scientists during the last decade, where the distortions are more likely to be noticeable to any viewer. With this consideration, we proposed a novel STDM watermarking method for a monochrome image by exploiting a visual saliency-based JND model. In our proposed JND model, a simple VS model is employed as a feature to reflect the importance of a local region and compute the final JND map. Extensive experiments performed on the classic image databases demonstrate that the proposed watermarking scheme works better in terms of the robustness than other related methods.
- Subjects :
- Computer science
Just noticeable distortion
Data_MISCELLANEOUS
ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION
STDM
02 engineering and technology
visual saliency
Image (mathematics)
Robustness (computer science)
0202 electrical engineering, electronic engineering, information engineering
Computer vision
Digital watermarking
Visual saliency
lcsh:T58.5-58.64
lcsh:Information technology
business.industry
watermarking
Visibility (geometry)
020206 networking & telecommunications
JND
Feature (computer vision)
Dither modulation
020201 artificial intelligence & image processing
Artificial intelligence
business
Information Systems
Subjects
Details
- Language :
- English
- ISSN :
- 20782489
- Database :
- OpenAIRE
- Journal :
- Information; Volume 8; Issue 3; Pages: 103
- Accession number :
- edsair.doi.dedup.....a764d03b5d0a10cec8fbd65a5410000e
- Full Text :
- https://doi.org/10.3390/info8030103