Perceptual Watermarking for Discrete Shearlet Transform

Baharak Ahmaderaghi; Jesus Martinez Del Rincon; Fatih Kurugollu; Ahmed Bouridane

doi:10.1109/EUVIP.2014.7018398

Perceptual Watermarking for Discrete Shearlet Transform

Baharak Ahmaderaghi, Jesus Martinez Del Rincon, Fatih Kurugollu, Ahmed Bouridane

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

6 Citations (Scopus)

418 Downloads (Pure)

Abstract

This paper presents a new perceptual watermarking model for Discrete Shearlet transform (DST). DST provides the optimal representation [10] of the image features based on multi-resolution and multi-directional analysis. This property can be exploited on for watermark embedding to achieve the watermarking imperceptibility by introducing the human visual system using Chou’s model. In this model, a spatial JND profile is adapted to fit the sub-band structure. The combination of DST and the Just-Noticeable Distortion (JND) profile improves the levels of robustness against certain attacks while minimizing the distortion; by assigning a visibility threshold of distortion to each DST sub-band coefficient in the case of grey scale image watermarking.

Original language	English
Title of host publication	2014 5th European Workshop on Visual Information Processing (EUVIP)
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1-6
Number of pages	6
ISBN (Print)	978-147994572-6
DOIs	https://doi.org/10.1109/EUVIP.2014.7018398
Publication status	Published - 12 Dec 2014
Event	European Workshop on Visual Information Processing - Paris, France Duration: 10 Dec 2014 → 12 Dec 2014

Conference

Conference	European Workshop on Visual Information Processing
Country/Territory	France
City	Paris
Period	10/12/2014 → 12/12/2014

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10.1109/EUVIP.2014.7018398

Perceptual Watermarking for Discrete Shearlet Transform
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Accepted author manuscript, 1.47 MB

R1118ECI: Centre for Secure Information Technologies (CSIT)
McCanny, J. V., Cowan, C., Crookes, D., Fusco, V., Linton, D., Liu, W., Miller, P., O'Neill, M., Scanlon, W. & Sezer, S.
01/08/2009 → 30/06/2014
Project: Research

Cite this

@inproceedings{48a726d2792c4c579c389198283c31ea,

title = "Perceptual Watermarking for Discrete Shearlet Transform",

abstract = "This paper presents a new perceptual watermarking model for Discrete Shearlet transform (DST). DST provides the optimal representation [10] of the image features based on multi-resolution and multi-directional analysis. This property can be exploited on for watermark embedding to achieve the watermarking imperceptibility by introducing the human visual system using Chou{\textquoteright}s model. In this model, a spatial JND profile is adapted to fit the sub-band structure. The combination of DST and the Just-Noticeable Distortion (JND) profile improves the levels of robustness against certain attacks while minimizing the distortion; by assigning a visibility threshold of distortion to each DST sub-band coefficient in the case of grey scale image watermarking.",

author = "Baharak Ahmaderaghi and {Martinez Del Rincon}, Jesus and Fatih Kurugollu and Ahmed Bouridane",

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language = "English",

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pages = "1--6",

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publisher = "Institute of Electrical and Electronics Engineers Inc.",

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Ahmaderaghi, B , Martinez Del Rincon, J, Kurugollu, F & Bouridane, A 2014, Perceptual Watermarking for Discrete Shearlet Transform. in 2014 5th European Workshop on Visual Information Processing (EUVIP). Institute of Electrical and Electronics Engineers Inc., pp. 1-6, European Workshop on Visual Information Processing, Paris, France, 10/12/2014. https://doi.org/10.1109/EUVIP.2014.7018398

Perceptual Watermarking for Discrete Shearlet Transform. / Ahmaderaghi, Baharak ; Martinez Del Rincon, Jesus; Kurugollu, Fatih; Bouridane, Ahmed.

2014 5th European Workshop on Visual Information Processing (EUVIP). Institute of Electrical and Electronics Engineers Inc., 2014. p. 1-6.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

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AU - Ahmaderaghi, Baharak

AU - Martinez Del Rincon, Jesus

AU - Kurugollu, Fatih

AU - Bouridane, Ahmed

PY - 2014/12/12

Y1 - 2014/12/12

N2 - This paper presents a new perceptual watermarking model for Discrete Shearlet transform (DST). DST provides the optimal representation [10] of the image features based on multi-resolution and multi-directional analysis. This property can be exploited on for watermark embedding to achieve the watermarking imperceptibility by introducing the human visual system using Chou’s model. In this model, a spatial JND profile is adapted to fit the sub-band structure. The combination of DST and the Just-Noticeable Distortion (JND) profile improves the levels of robustness against certain attacks while minimizing the distortion; by assigning a visibility threshold of distortion to each DST sub-band coefficient in the case of grey scale image watermarking.

AB - This paper presents a new perceptual watermarking model for Discrete Shearlet transform (DST). DST provides the optimal representation [10] of the image features based on multi-resolution and multi-directional analysis. This property can be exploited on for watermark embedding to achieve the watermarking imperceptibility by introducing the human visual system using Chou’s model. In this model, a spatial JND profile is adapted to fit the sub-band structure. The combination of DST and the Just-Noticeable Distortion (JND) profile improves the levels of robustness against certain attacks while minimizing the distortion; by assigning a visibility threshold of distortion to each DST sub-band coefficient in the case of grey scale image watermarking.

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DO - 10.1109/EUVIP.2014.7018398

M3 - Conference contribution

SN - 978-147994572-6

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BT - 2014 5th European Workshop on Visual Information Processing (EUVIP)

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - European Workshop on Visual Information Processing

Y2 - 10 December 2014 through 12 December 2014

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Perceptual Watermarking for Discrete Shearlet Transform

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R1118ECI: Centre for Secure Information Technologies (CSIT)

Cite this