Visual attention-based image watermarking
- Submitting institution
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Sheffield Hallam University
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 1777
- Type
- D - Journal article
- DOI
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10.1109/ACCESS.2016.2627241
- Title of journal
- IEEE Access
- Article number
- -
- First page
- 8002
- Volume
- 4
- Issue
- -
- ISSN
- 2169-3536
- Open access status
- Compliant
- Month of publication
- November
- Year of publication
- 2016
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
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2
- Research group(s)
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-
- Citation count
- 24
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Funded by EPSRC through a Dorothy Hodgkin Postgraduate Award, Grant EP/K009931/1 and a Digital Catapult researchers in residence fellowship. In their survey, Benois-Pineau and Mitrea (IEEE, 2017) report that the work advances the visual attention model in the DWT domain. Khan et al. (ICA, 2019) state that “[Bhowmik has] achieved a high perceptible image which is also highly robust as the outcome.” Singh et al. (2019) favourably review the technique. In Sharma, Chirag, and Bhaskar’s review (Materials Today, 2020) they found that Bhowmik’s saliency design outperforms the existing world-class technique in joint saliency detection and minimizes the intricacy of computation.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -