A hybrid scheme for robust color image watermarking using DSWT in DCT domain

Al-Afandy, Khalid A.; Faragallah, Osama S.; El-Rabaie, El-Sayed M.; El‐Samie, Fathi E. Abd; Elmhalawy, Ahmed

doi:10.1109/cist.2016.7805088

Cited by 6 publications

(7 citation statements)

References 6 publications

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“…But, this method cannot resist against cropping and rotation attack. The method proposed by Al-Afandy et al [11] proposed method shows good robustness and the NC values of this range from 0.9977 to 0.9997. Our proposed method shows higher NC values than these method against various attacks.…”

Section: Robustnessmentioning

confidence: 96%

“…This method has an average PSNR value of 34.4356. Al-Afandy et al [11] used discrete stationary wavelet transform (DSWT) in the DCT domain to embed watermark. This method has an average PSNR value of 33.1474 and ranges from 29 to 36.…”

Section: Digital Image and Video Watermarking And Steganographymentioning

confidence: 99%

“…The peak signal-to-noise ratio (PSNR) and structural similarity (SSIM) of the proposed method range from 47.4997 to 51.8848 and 0.9989 to 0.9998, respectively. On the other hand, PSNR and SSIM of the recent methods [4,11] range from 29.5667 to 34.4495 and 0.9507 to 0.9907, respectively. The normalized correlation (NC) of the proposed method for various attacks ranges from 0.9939 to 1, in contrast to the recent methods whose NC range from 0.0020 to 0.9996.…”

Section: Introductionmentioning

confidence: 99%

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Color Image Watermarking Based on Radon Transform and Jordan Decomposition

Dhar¹,

Hasan²,

Shimamura³

2018

Digital Image and Video Watermarking and Steganography [Working Title]

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Digital watermarking has been widely used for ownership identification and copyright protection. In this chapter, a color image watermarking method based on Radon transform (RT) and Jordan decomposition (JD) is proposed. Initially, the host color image is converted into L*a*b* color space. Then, the b* channel is selected and it is divided into 16 Â 16 non-overlapping blocks. RT is applied to each of these blocks. JD is applied to the selected RT coefficients of each block represented in m Â n matrix. Watermark data is embedded in the coefficients of the similarity transform matrix obtained from JD using a new quantization equation. Experimental results indicate that the proposed method is highly robust against various attacks such as noise addition, cropping, filtering, blurring, rotation, JPEG compression etc. In addition, it provides high quality watermarked images. Moreover, it shows superior performance than the state-of-the-art methods reported recently in terms of imperceptibility and robustness.

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Section: Robustnessmentioning

confidence: 96%

Section: Digital Image and Video Watermarking And Steganographymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Color Image Watermarking Based on Radon Transform and Jordan Decomposition

Dhar¹,

Hasan²,

Shimamura³

2018

Digital Image and Video Watermarking and Steganography [Working Title]

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“…The classical methods include such methods as the least significant bit method [ 9 ], the mask method [ 17 ], and frequency-domain manipulations (discrete cosine transform [ 18 ], discrete sine transform [ 19 ], discrete wavelet transform [ 10 ], discrete Fourier transform [ 20 ], and hybrid domains [ 21 , 22 , 23 ], among others). Assorted variations of the above-mentioned methods are used to embed watermarks in both static images and videos.…”

Section: Literature Reviewmentioning

confidence: 99%

“…The least significant bit method [ 9 , 32 ], as its name implies, uses the least significant bit of each channel value of a given colour palette, affecting the image slightly, but it is prone to losing the watermark due to all kinds of conversions. The whole image is also influenced by methods that manipulate the frequency domain [ 18 , 19 , 20 , 21 , 22 , 23 ], which are characterized by better survival despite various types of conversions than are those generated via the method of the least significant bit. The modification of the most convenient areas takes place in different methods.…”

Section: Literature Reviewmentioning

confidence: 99%

High-Quality Video Watermarking Based on Deep Neural Networks and Adjustable Subsquares Properties Algorithm

Kaczyński

Piotrowski

2022

Sensors

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This paper presents a method of high-capacity and transparent watermarking based on the usage of deep neural networks with the adjustable subsquares properties algorithm to encode the data of a watermark in high-quality video using the H.265/HEVC (High-Efficiency Video Coding) codec. The aim of the article is to present a method of embedding a watermark in a video with HEVC codec compression by making changes in a video in a way that is not noticeable to the naked eye. The method presented here is characterised by focusing on ensuring the accuracy of the original image in relation to the watermarked image, providing the transparency of the embedded watermark, while ensuring its survival after compression by the HEVC codec. The article includes a presentation of the practical results of watermark embedding with a built-in variation mechanism of its capacity and resistance, thanks to the adjustable subsquares properties algorithm. The obtained PSNR (peak signal-to-noise ratio) results are at the level of 40 dB or better. There is the possibility of the complete recovery of a watermark from a single frame compressed in the CRF (constant rate factor) range of up to 16, resulting in a BER (bit error rate) equal to 0 for the received watermark.

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