Digital Image Watermarking Method Based on LSB and DWT Hybrid Technique

Ghrare, Seddeq E.; Alamari, Ali; Emhemed, Hajer Abdulhkim

doi:10.1109/mi-sta54861.2022.9837586

Cited by 8 publications

(4 citation statements)

References 7 publications

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“…Classic methods can include methods, such as those based on the least significant bit [ 23 , 24 , 25 ] or methods based on frequency domain manipulation (discrete wavelet transform, discrete Fourier transform, discrete sine, and cosine transform) [ 10 , 26 , 27 , 28 , 29 , 30 , 31 ]. There are many modifications of these methods, such as a combination of the least significant bit method and those based on manipulation of the frequency domain, which includes publications concerning hybrid domains [ 23 , 32 , 33 , 34 ].…”

Section: Literature Reviewmentioning

confidence: 99%

High-Quality Video Watermarking Based on Deep Neural Networks for Video with HEVC Compression

Kaczyński

Piotrowski

Pietrow

2022

Sensors

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This article presents a method for transparent watermarking of high-capacity watermarked video under H.265/HEVC (High-Efficiency Video Coding) compression conditions while maintaining high-quality encoded image. The aim of this paper is to present a method for watermark embedding using neural networks under conditions of subjecting video to lossy compression of the HEVC codec using the YUV420p color model chrominance channel for watermarking. This paper presents a method for training a deep neural network to embed a watermark when a compression channel is present. The discussed method is characterized by high accuracy of the video with an embedded watermark compared to the original. The PSNR (peak signal-to-noise ratio) values obtained are over 44 dB. The watermark capacity is 96 bits for an image with a resolution of 128 × 128. The method enables the complete recovery of a watermark from a single video frame compressed by the HEVC codec within the range of compression values defined by the CRF (constant rate factor) up to 22.

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Section: Literature Reviewmentioning

confidence: 99%

High-Quality Video Watermarking Based on Deep Neural Networks for Video with HEVC Compression

Kaczyński

Piotrowski

Pietrow

2022

Sensors

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“…Still, the disadvantage is that watermarking is not robust. Ghrare et al [10] proposed a hybrid watermarking technique based on Least Significant Bit (LSB) and DWT, which divides the watermarked image into two parts and embeds them into the spatial and transform domains, respectively. This technique is resistant to Gaussian noise and JPEG compression but is less robust to geometric attacks.…”

Section: Introductionmentioning

confidence: 99%

“…Transform domain watermarking is performed by adjusting the coefficients of the image transform domain for watermark embedding [13,14], and this type of algorithm has the characteristics of more complex operations, less information capacity, but high resistance to attacks. The commonly used transform domains are DCT [4,6,15,[18][19][20][21], DWT [1,3,5,10,[15][16][17]22], DFT (Discrete Fourier Transform) [18], SVD (Singular Value Decomposition) [16,17,21] etc. Using a single transform domain does not meet the needs of all watermarking algorithms simultaneously, and to compensate for each other's shortcomings, most existing algorithms use hybrid domain techniques.…”

Section: Introductionmentioning

confidence: 99%

Robust zero‐watermarking algorithm based on discrete wavelet transform and daisy descriptors for encrypted medical image

Yuan,

Li,

Liu

et al. 2024

CAAI Trans on Intel Tech

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In the intricate network environment, the secure transmission of medical images faces challenges such as information leakage and malicious tampering, significantly impacting the accuracy of disease diagnoses by medical professionals. To address this problem, the authors propose a robust feature watermarking algorithm for encrypted medical images based on multi‐stage discrete wavelet transform (DWT), Daisy descriptor, and discrete cosine transform (DCT). The algorithm initially encrypts the original medical image through DWT‐DCT and Logistic mapping. Subsequently, a 3‐stage DWT transformation is applied to the encrypted medical image, with the centre point of the LL3 sub‐band within its low‐frequency component serving as the sampling point. The Daisy descriptor matrix for this point is then computed. Finally, a DCT transformation is performed on the Daisy descriptor matrix, and the low‐frequency portion is processed using the perceptual hashing algorithm to generate a 32‐bit binary feature vector for the medical image. This scheme utilises cryptographic knowledge and zero‐watermarking technique to embed watermarks without modifying medical images and can extract the watermark from test images without the original image, which meets the basic requirements of medical image watermarking. The embedding and extraction of watermarks are accomplished in a mere 0.160 and 0.411s, respectively, with minimal computational overhead. Simulation results demonstrate the robustness of the algorithm against both conventional attacks and geometric attacks, with a notable performance in resisting rotation attacks.

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“…The advantages and disadvantages of each scheme are used as inspiration to combine several transformations, or hybrids with new transformations to the scheme, or combined across different domains. For example, DCT with SVD scheme [39], DWT with SVD scheme [40], DWT with DCT scheme [41], SVD with Hadamard transform [42], DWT with LSB [43], SVD with DFT [44], DWT with DFT [45], SVD with SWT [46], SVD in spatial domain [47], hybrid SDV, DWT, and HVS [48], and many more hybrid image watermarking schemes. These hybrid examples show there are improvement opportunities to get better performances.…”

mentioning

confidence: 99%

Toward Achieving a Trade-Off for SVD-Based Image Watermarking Using Mojette Transform

Marjuni,

Shidik,

Syukur

et al. 2024

IEEE Access

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Imperceptibility and robustness are a part of trade-off components in image watermarking schemes and become one of the most studied in this field. Increasing imperceptibility usually will reduce the robustness, conversely, increasing the robustness may reduce the imperceptibility. This study is intended to overcome this challenge by proposing an image watermarking scheme using the Mojette transform to increase both imperceptibility and robustness. This transform is derived from the Radon transform which has some advantages in geometrical representations that have benefits for imperceptibility and robustness analyses. For evaluation purposes, the performance of the Mojette transform is evaluated on an image watermarking scheme in the singular value decomposition as this domain is stable in response to various image processing operations and also has a simple computation. The use of the Mojette transform in the proposed method involves both main image watermarking processes, which are watermark embedding and extraction. Towards achieving the trade-off of the watermarking requirement, the embedding watermark is designed at the maximum capacity. This means that the watermark is designed at the same size as the host image although it is embedded in various levels of scale factor. The watermarked image is then evaluated in the imperceptibility aspect, and the extracted watermark is evaluated in the robustness aspect after some attacks are applied to the watermarked images. Experimental results on some test images show that embedding the watermark at the maximum size using the proposed method kept producing a good perceptible watermarked image without reducing imperceptibility and robustness. For example, the imperceptibility of the watermarked image at 1% of the embedded scale factor could produce the visual quality at 45.2373 dB and the watermark could be extracted well although some attacks have occurred on the watermarked image. Almost all of the extracted watermarks after being distorted by nosing, filtering, compression, rotation, cropping, and flipping attacks have normalized correlation coefficients above 95%. Although the payload capacity of the watermark still needs further analysis, however, this study shows that the Mojette transform can contribute toward achieving the trade-off in the image watermarking requirements.INDEX TERMS Image watermarking, singular value decomposition, Mojette transform, watermarking scheme trade-off, imperceptibility, robustness, payload capacity. I. INTRODUCTIONData and information in the current digital era are commonly expressed in digital forms, such as text, images, audio,The associate editor coordinating the review of this manuscript and approving it for publication was Siddhartha Bhattacharyya .and video [1]. Compared to other digital formats, digital images dominate their use in practice, such as in business, health, social media, military, education, government, and many more. This is because the use of images is more effective and practiced. In terms of size, digital imag...

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Digital Image Watermarking Method Based on LSB and DWT Hybrid Technique

Cited by 8 publications

References 7 publications

High-Quality Video Watermarking Based on Deep Neural Networks for Video with HEVC Compression

High-Quality Video Watermarking Based on Deep Neural Networks for Video with HEVC Compression

Robust zero‐watermarking algorithm based on discrete wavelet transform and daisy descriptors for encrypted medical image

Toward Achieving a Trade-Off for SVD-Based Image Watermarking Using Mojette Transform

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