An Efficient Watermarking Approach Based on LL and HH Edges of DWT–SVD

Abstract

Digital watermarking is playing a vital role in the improvement of authentication, security, and copyright protection in today’s digital transformation. The performance of this technique is shown to be impressive around the globe. Text, audio, video, and image data are acted as watermarks in the digital platform. In this article, a hybrid watermarking scheme is proposed to furnish the robustness and protection of digital data. This hybrid scheme is a form of discrete wavelet transform (DWT) and singular value decomposition (SVD). The embedding and extracting features are carried out through multi-level operations of DWT and SVD. Various attacks are added to the proposed method to justify the robustness of the watermark. In the end, the suggested approach is contrasted with existing methods to confirm the supremacy.

A sophisticated and provably grayscale image watermarking system using DWT-SVD domain

“…As is observed from this table, especially compared to the methods of [29,31,49,52,[58][59][60][61][62]64], our proposal obtains better results in terms of PSNR and SSIM. For instance, the proposed method significantly outperforms [29] by 4.2946 dB and 0.91%, respectively, in PSNR and SSIM for watermarked image; 9.8433 dB and 0.62%, respectively, in PSNR and NC for extracted watermark. [57] and [63] also obtain good invisibility, and their average PSNRs are greater than 55 dB.…”

“…Figure 6a1-g1 illustrates the extracted watermarks from the watermarked images, and the subsequent Table 3 conveys all their numerical results between original and extracted watermark. As can be seen in this table, maximum SSIM Table 5 indicates the comparison of the watermarked image and extracted watermark for the proposed method against several baseline approaches (see [29,31,49,52,[57][58][59][60][61][62][63][64] and references therein); in which all methods used 'Lena' as a test image. As is observed from this table, especially compared to the methods of [29,31,49,52,[58][59][60][61][62]64], our proposal obtains better results in terms of PSNR and SSIM.…”

“…As can be seen in this table, maximum SSIM Table 5 indicates the comparison of the watermarked image and extracted watermark for the proposed method against several baseline approaches (see [29,31,49,52,[57][58][59][60][61][62][63][64] and references therein); in which all methods used 'Lena' as a test image. As is observed from this table, especially compared to the methods of [29,31,49,52,[58][59][60][61][62]64], our proposal obtains better results in terms of PSNR and SSIM. For instance, the proposed method significantly outperforms [29] by 4.2946 dB and 0.91%, respectively, in PSNR and SSIM for watermarked image; 9.8433 dB and 0.62%, respectively, in PSNR and NC for extracted watermark.…”

“…Consequently, many image watermarking techniques combining these two transform methods have been proposed. For example, Yasmeen and Uddin [29] proposed an improved DWT-SVD-based hybrid approach to further ensure the robustness and protection of digital data. This method contrasted with existing schemes and proved to be a good mechanism for both grayscale and color images.…”

Secure Transmission of EEG Data Using Watermarking Algorithm for the Detection of Epileptical Seizures

“…By enhancing the level of DWT, performance can be improved. In DWT based watermarking algorithm, it decomposes the two dimensional signal in to various frequency sub-bands namely LL, LH, HL, HH [30]. Now, according to level of DWT, respective subbands are again decomposing into further sub-band like LL sub-band may decomposes in to LL2, LH2, HL2, HH2.…”