Combining Haar Wavelet and Karhunen-Loeve Transform for Robust and Imperceptible Data Hiding Using Digital Images

Abstract In this paper, we present an introduction of digital image watermarking followed by important characteristics and potential applications of digital watermarks. Further, recent state-of-the-art watermarking techniques as reported by noted authors are discussed in brief. It includes the performance comparison of reported transform/spatial domain based watermarking techniques presented in tabular form. This comprehensive survey will be significant for researchers who will be able to implement more efficient watermarking techniques. Moreover, we present a robust watermarking technique using fusion of discrete wavelet transform (DWT) and Karhunen-Loeve transform for digital images. Further, visual quality of the watermarked image is enhanced by using different image de-noising techniques. The results are obtained by varying the gain factor, size of the image watermark, different DWT sub-bands, and image processing attacks. Experimental results demonstrate that the method is imperceptible and robust for different image processing attacks.

Download Full-text

FPGA Implementation of Digital Images Watermarking System Based on Discrete Haar Wavelet Transform

Security and Communication Networks ◽

10.1155/2019/1294267 ◽

2019 ◽

Vol 2019 ◽

pp. 1-17 ◽

Cited By ~ 6

Author(s):

Mohamed Ali Hajjaji ◽

Mohamed Gafsi ◽

Abdessalem Ben Abdelali ◽

Abdellatif Mtibaa

Keyword(s):

Wavelet Transform ◽

High Performance ◽

Large Scale ◽

Image Watermarking ◽

Haar Wavelet ◽

Discrete Wavelet ◽

Haar Wavelet Transform ◽

Integration Architecture ◽

Field Programmable ◽

Scale Integration

In this paper we propose a novel and efficient hardware implementation of an image watermarking system based on the Haar Discrete Wavelet Transform (DWT). DWT is used in image watermarking to hide secret pieces of information into a digital content with a good robustness. The main advantage of Haar DWT is the frequencies separation into four subbands (LL, LH, HL, and HH) which can be treated independently. This permits ensuring a better compromise between robustness and visibility factors. A Field Programmable Gate Array (FPGA) that is based on a very large scale integration architecture of the watermarking algorithm is developed to accelerate media authentication. A hardware cosimulation strategy using the Matlab-Xilinx system generator (XSG) was applied to prove the validity of the suggested implementation. The hardware cosimulation results show the effectiveness of the developed architecture in terms of visibility and robustness against several attacks. The proposed hardware system presents also a high performance in terms of the operating speed.

Download Full-text

A Robust and Oblivious Watermarking Method Using Maximum Wavelet Coefficient Modulation and Genetic Algorithm

Modeling and Simulation in Engineering - Selected Problems ◽

10.5772/intechopen.93832 ◽

2020 ◽

Author(s):

Surya Prasada Rao Borra ◽

Kongara Ramanjaneyulu ◽

K. Raja Rajeswari

Keyword(s):

Genetic Algorithm ◽

Wavelet Coefficient ◽

Image Watermarking ◽

Substantial Improvement ◽

Performance Comparison ◽

Cover Image ◽

Discrete Wavelet ◽

Content Authentication ◽

Binary Images ◽

Watermark Embedding

An image watermarking method using Discrete Wavelet Transform (DWT) and Genetic Algorithm (GA) is presented for applications like content authentication and copyright protection. This method is robust to various image attacks. For watermark detection/extraction, the cover image is not essential. Gray scale images of size 512 × 512 as cover image and binary images of size 64 × 64 as watermark are used in the simulation of the proposed method. Watermark embedding is done in the DWT domain. 3rd and 2nd level detail sub-band coefficients are selected for further processing. Selected coefficients are arranged in different blocks. The size of the block and the number blocks depends on the size of the watermark. One watermark bit is embedded in each block. Then, inverse DWT operation is performed to get the required watermarked image. This watermarked image is used for transmission and distribution purposes. In case of any dispute over the ownership, the hidden watermark is decoded to solve the problem. Threshold-based method is used for watermark extraction. Control parameters are identified and optimized based on GA for targeted performance in terms of PSNR and NCC. Performance comparison is done with the existing works and substantial improvement is witnessed.

Download Full-text

Combining Haar Wavelet and Karhunen Loeve Transforms for Medical Images Watermarking

BioMed Research International ◽

10.1155/2014/313078 ◽

2014 ◽

Vol 2014 ◽

pp. 1-15 ◽

Cited By ~ 14

Author(s):

Mohamed Ali Hajjaji ◽

El-Bay Bourennane ◽

Abdessalem Ben Abdelali ◽

Abdellatif Mtibaa

Keyword(s):

Fuzzy Inference ◽

Medical Images ◽

Haar Wavelet ◽

Discrete Wavelet ◽

Correct Identification ◽

Hidden Information ◽

Inference System ◽

Optimal Value ◽

Karhunen Loeve Transform ◽

Set Up

This paper presents a novel watermarking method, applied to the medical imaging domain, used to embed the patient’s data into the corresponding image or set of images used for the diagnosis. The main objective behind the proposed technique is to perform the watermarking of the medical images in such a way that the three main attributes of the hidden information (i.e., imperceptibility, robustness, and integration rate) can be jointly ameliorated as much as possible. These attributes determine the effectiveness of the watermark, resistance to external attacks, and increase the integration rate. In order to improve the robustness, a combination of the characteristics of Discrete Wavelet and Karhunen Loeve Transforms is proposed. The Karhunen Loeve Transform is applied on the subblocks (sized8×8) of the different wavelet coefficients (in the HL2, LH2, and HH2 subbands). In this manner, the watermark will be adapted according to the energy values of each of the Karhunen Loeve components, with the aim of ensuring a better watermark extraction under various types of attacks. For the correct identification of inserted data, the use of an Errors Correcting Code (ECC) mechanism is required for the check and, if possible, the correction of errors introduced into the inserted data. Concerning the enhancement of the imperceptibility factor, the main goal is to determine the optimal value of the visibility factor, which depends on several parameters of the DWT and the KLT transforms. As a first step, a Fuzzy Inference System (FIS) has been set up and then applied to determine an initial visibility factor value. Several features extracted from the Cooccurrence matrix are used as an input to the FIS and used to determine an initial visibility factor for each block; these values are subsequently reweighted in function of the eigenvalues extracted from each subblock. Regarding the integration rate, the previous works insert one bit per coefficient. In our proposal, the integration of the data to be hidden is 3 bits per coefficient so that we increase the integration rate by a factor of magnitude 3.

Download Full-text

A Hybrid Robust Image Watermarking Method Based on DWT-DCT and SIFT for Copyright Protection

Journal of Imaging ◽

10.3390/jimaging7100218 ◽

2021 ◽

Vol 7 (10) ◽

pp. 218

Author(s):

Mohamed Hamidi ◽

Mohamed El Haziti ◽

Hocine Cherifi ◽

Mohammed El Hassouni

Keyword(s):

Image Processing ◽

Wavelet Transform ◽

Discrete Wavelet Transform ◽

Discrete Cosine Transform ◽

Image Watermarking ◽

Extraction Process ◽

Alternative Methods ◽

Discrete Wavelet ◽

Scale Invariant ◽

Cosine Transform

In this paper, a robust hybrid watermarking method based on discrete wavelet transform (DWT), discrete cosine transform (DCT), and scale-invariant feature transformation (SIFT) is proposed. Indeed, it is of prime interest to develop robust feature-based image watermarking schemes to withstand both image processing attacks and geometric distortions while preserving good imperceptibility. To this end, a robust watermark is embedded in the DWT-DCT domain to withstand image processing manipulations, while SIFT is used to protect the watermark from geometric attacks. First, the watermark is embedded in the middle band of the discrete cosine transform (DCT) coefficients of the HL1 band of the discrete wavelet transform (DWT). Then, the SIFT feature points are registered to be used in the extraction process to correct the geometric transformations. Extensive experiments have been conducted to assess the effectiveness of the proposed scheme. The results demonstrate its high robustness against standard image processing attacks and geometric manipulations while preserving a high imperceptibility. Furthermore, it compares favorably with alternative methods.

Download Full-text

Blind and Secured Adaptive Digital Image Watermarking Approach for High Imperceptibility and Robustness

Entropy ◽

10.3390/e23121650 ◽

2021 ◽

Vol 23 (12) ◽

pp. 1650

Author(s):

Priyanka Singh ◽

Kilari Jyothsna Devi ◽

Hiren Kumar Thakkar ◽

José Santamaría

Keyword(s):

Digital Image ◽

Digital Images ◽

Image Watermarking ◽

Rapid Development ◽

Image Transmission ◽

Performance Comparison ◽

Computational Time ◽

Digital Image Watermarking ◽

Bee Colony ◽

Improved Performance

In the past decade, rapid development in digital communication has led to prevalent use of digital images. More importantly, confidentiality issues have also come up recently due to the increase in digital image transmission across the Internet. Therefore, it is necessary to provide high imperceptibility and security to digitally transmitted images. In this paper, a novel blind digital image watermarking scheme is introduced tackling secured transmission of digital images, which provides a higher quality regarding both imperceptibility and robustness parameters. A block based hybrid IWT- SVD transform is implemented for robust transmission of digital images. To ensure high watermark security, the watermark is encrypted using a Pseudo random key which is generated adaptively from cover and watermark images. An encrypted watermark is embedded in randomly selected low entropy blocks to increase the security as well as imperceptibility. Embedding positions within the block are identified adaptively using a Blum–Blum–Shub Pseudo random generator. To ensure higher visual quality, Initial Scaling Factor (ISF) is chosen adaptively from a cover image using image range characteristics. ISF can be optimized using Nature Inspired Optimization (NIO) techniques for higher imperceptibility and robustness. Specifically, the ISF parameter is optimized by using three well-known and novel NIO-based algorithms such as Genetic Algorithms (GA), Artificial Bee Colony (ABC), and Firefly Optimization algorithm. Experiments were conducted for the proposed scheme in terms of imperceptibility, robustness, security, embedding rate, and computational time. Experimental results support higher effectiveness of the proposed scheme. Furthermore, performance comparison has been done with some of the existing state-of-the-art schemes which substantiates the improved performance of the proposed scheme.

Download Full-text

A High Result in Wavelet Watermarking Using Singular Value Decomposition

Kinetik Game Technology Information System Computer Network Computing Electronics and Control ◽

10.22219/kinetik.v4i3.729 ◽

2019 ◽

pp. 269-276

Author(s):

Wellia Shinta Sari ◽

Christy Atika Sari

Keyword(s):

Singular Value Decomposition ◽

Digital Images ◽

Image Watermarking ◽

Singular Value ◽

Digital Data ◽

Discrete Wavelet ◽

Good Image Quality ◽

Host Image ◽

High Result ◽

Value Decomposition

Internet that has developed into a good distribution tool for digital data, causing a large increase in digital data sharing, especially in the form of digital images, and causing problems that need attention. One of them is about copyright protection. Watermarking is one technique that aims to protect digital image copyright. In this study, watermarking was carried out using the Discrete Wavelet Transform (DWT) and Singular Value Decomposition (SVD) algorithms in digital images with different file extensions. Transformation of 2 levels of DWT and SVD on the host image and SVD transformation on the watermarked image that inserted in the LL2 sub-band of the host image. Watermarking with the proposed method produces good image quality with PSNR values exceeding 40 dB, SSIM reaching 0.99 and NCC reaching 1. This shows a robust and imperceptible watermarking image.

Download Full-text

SOME NOTES ON THE APPLICATION OF DISCRETE WAVELET TRANSFORM IN IMAGE PROCESSING

10.1063/1.3591899 ◽

2011 ◽

Author(s):

Egydio C. S. Caria ◽

Trajano A. de A. Costa ◽

João Marcos A. Rebello ◽

Donald O. Thompson ◽

Dale E. Chimenti

Keyword(s):

Image Processing ◽

Wavelet Transform ◽

Discrete Wavelet Transform ◽

Discrete Wavelet

Download Full-text

Quantum generative adversarial networks for learning and loading quantum image in noisy environment

Modern Physics Letters B ◽

10.1142/s0217984921503607 ◽

2021 ◽

pp. 2150360

Author(s):

Wanghao Ren ◽

Zhiming Li ◽

Yiming Huang ◽

Runqiu Guo ◽

Lansheng Feng ◽

...

Keyword(s):

Image Processing ◽

Quantum Circuit ◽

Quantum Image Processing ◽

Quantum Circuits ◽

Generative Adversarial Networks ◽

Channel Noise ◽

Quantum Image ◽

Adversarial Networks ◽

Potential Applications ◽

Classical Image

Quantum machine learning is expected to be one of the potential applications that can be realized in the near future. Finding potential applications for it has become one of the hot topics in the quantum computing community. With the increase of digital image processing, researchers try to use quantum image processing instead of classical image processing to improve the ability of image processing. Inspired by previous studies on the adversarial quantum circuit learning, we introduce a quantum generative adversarial framework for loading and learning a quantum image. In this paper, we extend quantum generative adversarial networks to the quantum image processing field and show how to learning and loading an classical image using quantum circuits. By reducing quantum gates without gradient changes, we reduced the number of basic quantum building block from 15 to 13. Our framework effectively generates pure state subject to bit flip, bit phase flip, phase flip, and depolarizing channel noise. We numerically simulate the loading and learning of classical images on the MINST database and CIFAR-10 database. In the quantum image processing field, our framework can be used to learn a quantum image as a subroutine of other quantum circuits. Through numerical simulation, our method can still quickly converge under the influence of a variety of noises.

Download Full-text