Cargando…
A Computational Model of Watermark Algorithmic Robustness Capable of Resisting Image Cropping for Remote Sensing Images
Various watermarking algorithms have been studied to better enable the copyright protection of remote sensing images. The robustness of such algorithms against image cropping attacks has subsequently been verified mainly by various experiments. However, to date, the experimental results are subject...
Autores principales: | , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6068955/ https://www.ncbi.nlm.nih.gov/pubmed/29966309 http://dx.doi.org/10.3390/s18072096 |
_version_ | 1783343385952649216 |
---|---|
author | Tong, Deyu Ren, Na Shi, Wenzhong Zhu, Changqing |
author_facet | Tong, Deyu Ren, Na Shi, Wenzhong Zhu, Changqing |
author_sort | Tong, Deyu |
collection | PubMed |
description | Various watermarking algorithms have been studied to better enable the copyright protection of remote sensing images. The robustness of such algorithms against image cropping attacks has subsequently been verified mainly by various experiments. However, to date, the experimental results are subject to the differences in experimental factors and computational resource costs. Hence, the study presented in this paper proposes a robustness computation model of watermarking remote sensing images in terms of the image cropping attack. The robustness computation model consists of three parts: analysis principles, an evaluation index, and a computation method. The robustness analysis principles are provided based on the salient features of watermarking remote sensing images and attacking properties. A probability-based evaluation index is then defined to more comprehensively measure the robustness of different algorithms. The computation method developed in this study is based on permutations and the inclusion-exclusion principle to theoretically calculate robustness. The experiments conducted to verify the effectiveness of the computation model, revealed true closeness between both the calculated and experimental results. Finally, the relationships between the robustness and the different parameters used in the watermarking algorithms are investigated by using the proposed computation model. |
format | Online Article Text |
id | pubmed-6068955 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-60689552018-08-07 A Computational Model of Watermark Algorithmic Robustness Capable of Resisting Image Cropping for Remote Sensing Images Tong, Deyu Ren, Na Shi, Wenzhong Zhu, Changqing Sensors (Basel) Article Various watermarking algorithms have been studied to better enable the copyright protection of remote sensing images. The robustness of such algorithms against image cropping attacks has subsequently been verified mainly by various experiments. However, to date, the experimental results are subject to the differences in experimental factors and computational resource costs. Hence, the study presented in this paper proposes a robustness computation model of watermarking remote sensing images in terms of the image cropping attack. The robustness computation model consists of three parts: analysis principles, an evaluation index, and a computation method. The robustness analysis principles are provided based on the salient features of watermarking remote sensing images and attacking properties. A probability-based evaluation index is then defined to more comprehensively measure the robustness of different algorithms. The computation method developed in this study is based on permutations and the inclusion-exclusion principle to theoretically calculate robustness. The experiments conducted to verify the effectiveness of the computation model, revealed true closeness between both the calculated and experimental results. Finally, the relationships between the robustness and the different parameters used in the watermarking algorithms are investigated by using the proposed computation model. MDPI 2018-06-29 /pmc/articles/PMC6068955/ /pubmed/29966309 http://dx.doi.org/10.3390/s18072096 Text en © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Tong, Deyu Ren, Na Shi, Wenzhong Zhu, Changqing A Computational Model of Watermark Algorithmic Robustness Capable of Resisting Image Cropping for Remote Sensing Images |
title | A Computational Model of Watermark Algorithmic Robustness Capable of Resisting Image Cropping for Remote Sensing Images |
title_full | A Computational Model of Watermark Algorithmic Robustness Capable of Resisting Image Cropping for Remote Sensing Images |
title_fullStr | A Computational Model of Watermark Algorithmic Robustness Capable of Resisting Image Cropping for Remote Sensing Images |
title_full_unstemmed | A Computational Model of Watermark Algorithmic Robustness Capable of Resisting Image Cropping for Remote Sensing Images |
title_short | A Computational Model of Watermark Algorithmic Robustness Capable of Resisting Image Cropping for Remote Sensing Images |
title_sort | computational model of watermark algorithmic robustness capable of resisting image cropping for remote sensing images |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6068955/ https://www.ncbi.nlm.nih.gov/pubmed/29966309 http://dx.doi.org/10.3390/s18072096 |
work_keys_str_mv | AT tongdeyu acomputationalmodelofwatermarkalgorithmicrobustnesscapableofresistingimagecroppingforremotesensingimages AT renna acomputationalmodelofwatermarkalgorithmicrobustnesscapableofresistingimagecroppingforremotesensingimages AT shiwenzhong acomputationalmodelofwatermarkalgorithmicrobustnesscapableofresistingimagecroppingforremotesensingimages AT zhuchangqing acomputationalmodelofwatermarkalgorithmicrobustnesscapableofresistingimagecroppingforremotesensingimages AT tongdeyu computationalmodelofwatermarkalgorithmicrobustnesscapableofresistingimagecroppingforremotesensingimages AT renna computationalmodelofwatermarkalgorithmicrobustnesscapableofresistingimagecroppingforremotesensingimages AT shiwenzhong computationalmodelofwatermarkalgorithmicrobustnesscapableofresistingimagecroppingforremotesensingimages AT zhuchangqing computationalmodelofwatermarkalgorithmicrobustnesscapableofresistingimagecroppingforremotesensingimages |