Transform domain robust image-adaptive watermarking: Prevalent techniques and their evaluation

2015 ◽  
Author(s):  
Navneet Yadav ◽  
Kulbir Singh
Keyword(s):  
Transform Domain ◽  
Adaptive Watermarking ◽  
Robust Image

scholarly journals A Robust Image Watermarking Approach Using Cycle Variational Autoencoder

2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Qiang Wei ◽  
Hu Wang ◽  
Gongxuan Zhang
Keyword(s):  
Copyright Protection ◽  
Cloud Storage ◽  
Image Watermarking ◽  
Rapid Development ◽  
Transform Domain ◽  
Watermark Image ◽  
Visual Effects ◽  
Variational Autoencoder ◽  
Robust Image ◽  
Traditional Approaches

With the rapid development of Internet and cloud storage, data security sharing and copyright protection are becoming more and more important. In this paper, we introduce a robust image watermarking algorithm for copyright protection based on variational autoencoder networks. The proposed image watermarking embedding and extracting network consists of three parts: encoder subnetwork, decoder subnetwork, and detector subnetwork. In the training process, the encoder and decoder subnetworks learn a robust image representation model and further implement the embedding of 1-bit watermark image to the cover image. Meanwhile, the detector subnetwork learns to extract the 1-bit watermark image from the embedding image. Experimental results demonstrate that the watermarked images generated by the proposed algorithm have better visual effects and are more robust against geometric and noise attacks than traditional approaches in the transform domain.

Robust image registration using subspace method in Radon transform domain

Sensor Review ◽  
2019 ◽  
Vol 39 (5) ◽  
pp. 645-651
Author(s):  
Ning Wei ◽  
Yu He ◽  
Junqing Liu ◽  
Peng Chen
Keyword(s):  
Image Registration ◽  
Radon Transform ◽  
Median Filter ◽  
Least Square ◽  
Phase Correlation ◽  
Transform Domain ◽  
Registration Method ◽  
Content Type ◽  
Structural Differences ◽  
Robust Image

Purpose The purpose of this paper is to represent a robust image registration method to align noisy and deformed images in their Radon transform domain. Due to the limitation of imaging mechanism, the images are often highly noisy. Even worse, the objects in images have structural differences from time to time. Design/methodology/approach To eliminate these degressions, the proposed method is equipped with subspace-based power spectrum analysis algorithm for rotation estimation and a new global median filter least square algorithm for displacement computation. Findings Experiments on strongly noisy and degenerated images show that the proposed method exhibits better accuracy and robustness than phase correlation-based method. In addition, the method can also be applied to multi-modal registration, where the results are comparable to mutual information method but spending much less time. Originality/value A robust image registration method is proposed, which has better performance than traditional methods.

A robust image watermarking in contourlet transform domain

2017 ◽  
Author(s):  
Rajat Sharma ◽  
Abhishek Kumar Gupta ◽  
Deepak Singh ◽  
Vivek Singh Verma ◽  
Anuj Bhardwaj
Keyword(s):  
Image Watermarking ◽  
Contourlet Transform ◽  
Transform Domain ◽  
Robust Image

An improved robust image-adaptive watermarking with two watermarks using statistical decoder

2019 ◽  
Vol 79 (1-2) ◽  
pp. 183-217 ◽  
Author(s):  
Preeti Bhinder ◽  
Neeru Jindal ◽  
Kulbir Singh
Keyword(s):  
Adaptive Watermarking ◽  
Robust Image

Robust image hash in Radon transform domain for authentication

2011 ◽  
Vol 26 (6) ◽  
pp. 280-288 ◽  
Author(s):  
Yanqiang Lei ◽  
Yuangen Wang ◽  
Jiwu Huang
Keyword(s):  
Radon Transform ◽  
Transform Domain ◽  
Image Hash ◽  
Robust Image

A NEW CONTOURLET-DOMAIN BASED IMAGE WATERMARKING SCHEME RESILIENT TO GEOMETRICAL ATTACKS

2009 ◽  
Vol 07 (01) ◽  
pp. 115-130 ◽  
Author(s):  
OU-JUN LOU ◽  
XIANG-HAI WANG ◽  
ZHENG-XUAN WANG
Keyword(s):  
Signal Processing ◽  
Image Watermarking ◽  
Maximum Energy ◽  
Transform Domain ◽  
Feature Template ◽  
Robust Image ◽  
Common Signal ◽  
Watermarking Scheme ◽  
Significant Region ◽  
Geometrical Attacks

Coping with geometrical attacks in transform domain is crucial when we design a robust image watermarking scheme. In this paper, a novel contourlet-domain image watermarking scheme, which is robust to common signal processing and geometrical attacks, is proposed. First, the region with maximum energy in the directional subbands is considered for watermarking, i.e. the watermark can be embedded into the significant region as well as highly textured region of the host image. Then, for each coefficient of the selected subband, the strength factor was adaptively adjusted in terms of the energy of its parent and neighbor coefficients. Consequently, the tradeoff between the transparency and robustness of watermark can be achieved. Furthermore, the robust feature points, which can survive various signal processing and affine transformation, are extracted by using the Harris–Laplace detector. In watermark detection, the geometrical distortion of image is identified by using the feature template constructed during embedding phase, i.e. watermark resynchronization is performed. Experimental results show that the proposed watermark scheme is invisible and robust against common signal processing such as median filtering, sharpening, noise adding and JPEG compression, etc and geometrical attacks such as rotation, translation, scaling, row or column removal, shearing and local random bend, etc.

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