Digital image watermarking using partial pivoting lower and upper triangular decomposition into the wavelet domain Article Swipe
Nazeer Muhammad
,
Nargis Bibi
·
YOU?
·
· 2015
· Open Access
·
· DOI: https://doi.org/10.1049/iet-ipr.2014.0395
YOU?
·
· 2015
· Open Access
·
· DOI: https://doi.org/10.1049/iet-ipr.2014.0395
A digital image watermarking algorithm using partial pivoting lower and upper triangular (PPLU) decomposition is proposed. In this method, a digital watermark image is factorised into lower triangular, upper triangular and permutation matrices by PPLU decomposition. The permutation matrix is used as the valid key matrix for authentication of the rightful ownership of the watermark image. The product of the lower and upper triangular matrices is embedded into particular sub‐bands of a cover image that is decomposed by wavelet transform using the singular value decomposition. The weightage‐based differential evolution algorithm is used to achieve the possible scaling factor for obtaining the maximum possible robustness against various image processing operations and pirate attacks. The authors experiments show that the proposed algorithm is highly reliable with better imperceptibility of the embedded image and computationally efficient compared with recently existed methods.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1049/iet-ipr.2014.0395
- https://onlinelibrary.wiley.com/doi/pdfdirect/10.1049/iet-ipr.2014.0395
- OA Status
- bronze
- Cited By
- 63
- References
- 35
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2117814185
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W2117814185Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1049/iet-ipr.2014.0395Digital Object Identifier
- Title
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Digital image watermarking using partial pivoting lower and upper triangular decomposition into the wavelet domainWork title
- Type
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articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
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2015Year of publication
- Publication date
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2015-06-17Full publication date if available
- Authors
-
Nazeer Muhammad, Nargis BibiList of authors in order
- Landing page
-
https://doi.org/10.1049/iet-ipr.2014.0395Publisher landing page
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https://onlinelibrary.wiley.com/doi/pdfdirect/10.1049/iet-ipr.2014.0395Direct link to full text PDF
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YesWhether a free full text is available
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bronzeOpen access status per OpenAlex
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https://onlinelibrary.wiley.com/doi/pdfdirect/10.1049/iet-ipr.2014.0395Direct OA link when available
- Concepts
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Digital watermarking, Wavelet, Image (mathematics), Computer science, Domain (mathematical analysis), Decomposition, Computer vision, Artificial intelligence, Mathematics, Algorithm, Mathematical analysis, Chemistry, Organic chemistryTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
63Total citation count in OpenAlex
- Citations by year (recent)
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2025: 3, 2024: 2, 2023: 3, 2022: 1, 2021: 6Per-year citation counts (last 5 years)
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35Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.valid | 43 |
| abstract_inverted_index.value | 83 |
| abstract_inverted_index.(PPLU) | 12 |
| abstract_inverted_index.better | 124 |
| abstract_inverted_index.factor | 97 |
| abstract_inverted_index.highly | 121 |
| abstract_inverted_index.image. | 55 |
| abstract_inverted_index.matrix | 38, 45 |
| abstract_inverted_index.pirate | 110 |
| abstract_inverted_index.achieve | 93 |
| abstract_inverted_index.against | 104 |
| abstract_inverted_index.authors | 113 |
| abstract_inverted_index.digital | 1, 20 |
| abstract_inverted_index.existed | 136 |
| abstract_inverted_index.maximum | 101 |
| abstract_inverted_index.method, | 18 |
| abstract_inverted_index.partial | 6 |
| abstract_inverted_index.product | 57 |
| abstract_inverted_index.scaling | 96 |
| abstract_inverted_index.various | 105 |
| abstract_inverted_index.wavelet | 78 |
| abstract_inverted_index.attacks. | 111 |
| abstract_inverted_index.compared | 133 |
| abstract_inverted_index.embedded | 66, 128 |
| abstract_inverted_index.matrices | 32, 64 |
| abstract_inverted_index.methods. | 137 |
| abstract_inverted_index.pivoting | 7 |
| abstract_inverted_index.possible | 95, 102 |
| abstract_inverted_index.proposed | 118 |
| abstract_inverted_index.recently | 135 |
| abstract_inverted_index.reliable | 122 |
| abstract_inverted_index.rightful | 50 |
| abstract_inverted_index.singular | 82 |
| abstract_inverted_index.algorithm | 4, 89, 119 |
| abstract_inverted_index.efficient | 132 |
| abstract_inverted_index.evolution | 88 |
| abstract_inverted_index.obtaining | 99 |
| abstract_inverted_index.ownership | 51 |
| abstract_inverted_index.proposed. | 15 |
| abstract_inverted_index.transform | 79 |
| abstract_inverted_index.watermark | 21, 54 |
| abstract_inverted_index.decomposed | 76 |
| abstract_inverted_index.factorised | 24 |
| abstract_inverted_index.operations | 108 |
| abstract_inverted_index.particular | 68 |
| abstract_inverted_index.processing | 107 |
| abstract_inverted_index.robustness | 103 |
| abstract_inverted_index.triangular | 11, 29, 63 |
| abstract_inverted_index.experiments | 114 |
| abstract_inverted_index.permutation | 31, 37 |
| abstract_inverted_index.sub‐bands | 69 |
| abstract_inverted_index.triangular, | 27 |
| abstract_inverted_index.differential | 87 |
| abstract_inverted_index.watermarking | 3 |
| abstract_inverted_index.decomposition | 13 |
| abstract_inverted_index.authentication | 47 |
| abstract_inverted_index.decomposition. | 35, 84 |
| abstract_inverted_index.computationally | 131 |
| abstract_inverted_index.imperceptibility | 125 |
| abstract_inverted_index.weightage‐based | 86 |
| cited_by_percentile_year.max | 100 |
| cited_by_percentile_year.min | 89 |
| corresponding_author_ids | https://openalex.org/A5061889303 |
| countries_distinct_count | 3 |
| institutions_distinct_count | 2 |
| corresponding_institution_ids | https://openalex.org/I16076960, https://openalex.org/I4575257 |
| citation_normalized_percentile.value | 0.97494718 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | True |