Enhanced high capacity image steganography using discrete wavelet transform and the Laplacian pyramid

Rabie, Tamer; Baziyad, Mohammed; Kamel, Ibrahim

doi:10.1007/s11042-018-5713-2

Cited by 46 publications

(11 citation statements)

References 45 publications

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“…However, transform methods suffer from a traditional trade-off between capacity and imperceptibility. This relationship was exhaustively investigated by Rabie and Kamel [5], [16], [17] and Rabie et al [18], [19] for image-based steganography, but never before investigated in-depth for video-based steganography schemes.…”

Section: Related Workmentioning

confidence: 99%

The Pixogram: Addressing High Payload Demands for Video Steganography

Rabie

Baziyad

2019

IEEE Access

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This paper introduces the concept of a pixogram which makes possible a fresh approach to high payload video steganography. The pixogram allows for a new perspective by investigating the temporal changes that take place at the individual pixel level across frames of a video segment. Simply put, a pixogram has the property of converting highly uncorrelated spatial areas of individual frames of a video scene into highly correlated temporal segments by making use of the temporal correlation between the frames of the same scene in a given video segment, thus maximizing the redundant area suitable for hiding in the transform domain. Experimental results demonstrate the effectiveness of this new approach for increased payload capacity while maintaining visual fidelity of the stego-video as compared to competing video steganography schemes.

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Section: Related Workmentioning

confidence: 99%

The Pixogram: Addressing High Payload Demands for Video Steganography

Rabie

Baziyad

2019

IEEE Access

Self Cite

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“…For large-scale multimedia applications, Li et al proposed an image steganography technology that uses cosine transform to obtain an image steganography capacity of 21.5 bpp when the signal-to-noise ratio is 38.24 dB [ 28 ]. Another high-capacity image steganography scheme is proposed by Rabie et al [ 29 ], which uses the multi-scale Laplacian pyramid of the cover image in wavelet domain to realize data embedding, and they use the method of curve fitting adaptive region to find the appropriate hiding position in the DCT domain. Thanki et al proposed an image steganography technique based on Finite Ridge Transform (FRT) and Discrete Wavelet Transform (DWT).…”

Section: Introductionmentioning

confidence: 99%

Double-Matrix Decomposition Image Steganography Scheme Based on Wavelet Transform with Multi-Region Coverage

Ping

Yang

et al. 2022

Entropy

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On the basis of ensuring the quality and concealment of steganographic images, this paper proposes a double-matrix decomposition image steganography scheme with multi-region coverage, to solve the problem of poor extraction ability of steganographic images under attack or interference. First of all, the cover image is transformed by multi-wavelet transform, and the hidden region covering multiple wavelet sub-bands is selected in the wavelet domain of the cover image to embed the secret information. After determining the hidden region, the hidden region is processed by Arnold transform, Hessenberg decomposition, and singular-value decomposition. Finally, the secret information is embedded into the cover image by embedding intensity factor. In order to ensure robustness, the hidden region selected in the wavelet domain is used as the input of Hessenberg matrix decomposition, and the robustness of the algorithm is further enhanced by Hessenberg matrix decomposition and singular-value decomposition. Experimental results show that the proposed method has excellent performance in concealment and quality of extracted secret images, and secret information is extracted from steganographic images attacked by various image processing attacks, which proves that the proposed method has good anti-attack ability under different attacks.

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“…For image compression, various constraints are enforced; including processing power, data traffic and bandwidth, which can influence image quality (i.e., image degradation) and/or losses the embedded data are also compressed before transmission with the intention of transmission to speed [4]. Studies have also demonstrated the negative side of compressive photos of JPEG such as JPEG blockage, the product of the discrete cosine transform loss function dependent on 8 to 8 compression blocks normal JPEG [17], as well as lost details due to compressed picture deformation [18]. Nevertheless, this approach is subjected to multiple attacks, such as an additive white Gaussian noise (AWGN), image rescaling, JPEG distortion and a filter attack [19].…”

Section: Introductionmentioning

confidence: 99%

Securing data using deep hiding selected least significant bit and adaptive swarm algorithm

Aljidi

Perumal

Pitchay

2022

IJEECS

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The emphasis on data protection is improved in particular with respect to the transmission protocols utilized. Different research on numerous data protection areas such as authentication, encryption, hiding of data and validation were performed. In addition, a cybersecurity standard, such as IP-SEC, and secure sockets layer (SSL), were introduced to solve privacy infringement problems by applying encryption, authorization and protection to data exchanged and data stored in the cloud. This study suggests a new steganography algorithm, a data protection tool used to conceal massive amounts of data from graphic and statistic attacks in color images. The proposed algorithm is a multi-level steganography modified deep hiding/extracting technique (MDHET), which implements a selected least signified bit (SLSB) for color picture dispersal of the information. In addition, an accurate pixel location randomization feature has been applied. After MDHET, the predicted results will effectively conceal data up to 6 bpp (bit per pixel) with high safety levels by improving the quality of images. In addition, MDHET can be useful for encoding a deep series of images into one in which the testing procedure is carried out using regular reference images used in color image processing and compression analysis from different institutions.

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Enhanced high capacity image steganography using discrete wavelet transform and the Laplacian pyramid

Cited by 46 publications

References 45 publications

The Pixogram: Addressing High Payload Demands for Video Steganography

The Pixogram: Addressing High Payload Demands for Video Steganography

Double-Matrix Decomposition Image Steganography Scheme Based on Wavelet Transform with Multi-Region Coverage

Securing data using deep hiding selected least significant bit and adaptive swarm algorithm

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