scholarly journals A Robust Color Image Watermarking Algorithm Based on APDCBT and SSVD

Symmetry ◽  
2019 ◽  
Vol 11 (10) ◽  
pp. 1227 ◽  
Author(s):  
Xiaoyan Yu ◽  
Chengyou Wang ◽  
Xiao Zhou
Keyword(s):  
Singular Value Decomposition ◽  
Color Image ◽  
Image Watermarking ◽  
Median Filter ◽  
Coefficient Matrix ◽  
Singular Value ◽  
Color Images ◽  
Color Image Watermarking ◽  
Value Decomposition ◽  
Dc Coefficient

With the wide application of color images, watermarking for the copyright protection of color images has become a research hotspot. In this paper, a robust color image watermarking algorithm based on all phase discrete cosine biorthogonal transform (APDCBT) and shuffled singular value decomposition (SSVD) is proposed. The host image is transformed by the 8 × 8 APDCBT to obtain the direct current (DC) coefficient matrix, and then, the singular value decomposition (SVD) is performed on the DC matrix to embed the watermark. The SSVD and Fibonacci transform are mainly used at the watermark preprocessing stage to improve the security and robustness of the algorithm. The watermarks are color images, and a color quick response (QR) code with error correction mechanism is introduced to be a watermark to further improve the robustness. The watermark embedding and extraction processes are symmetrical. The experimental results show that the algorithm can effectively resist common image processing attacks, such as JPEG compression, Gaussian noise, salt and pepper noise, average filter, median filter, Gaussian filter, sharpening, scaling attacks, and a certain degree of rotation attacks. Compared with the color image watermarking algorithms considered in this paper, the proposed algorithm has better performance in robustness and imperceptibility.

scholarly journals SVD-Based Color Image Watermarking Using Discrete Wavelet Transform

2011 ◽  
Vol 1 ◽  
pp. 209-213
Author(s):  
Wang Sheng Fang ◽  
Rong Zhang ◽  
Yu Nan Li ◽  
Lu Lu Wu
Keyword(s):  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Color Image ◽  
Image Watermarking ◽  
Singular Value ◽  
Discrete Wavelet ◽  
Color Image Watermarking ◽  
Additional Advantage ◽  
Process Modification ◽  
Value Decomposition

For invisibility and robustness are difficult to reconcile, a combination of singular value decomposition (SVD) and the discrete wavelet transform (DWT) of the color image adaptive watermarking algorithm is proposed. In the embedding process, modification of the singular value of LL band and LH band exploited to the watermarking scheme which excellent preserves the quality. The additional advantage of the proposed technique is taking advantage of HVS which can adaptively regulate the watermark embedding strength. Experimental results show that the algorithm not only has better transparency, but also has good robustness such as noise, compression, filtering, cropping.

LWT-DCT based Image Watermarking Scheme using Normalized SVD

2020 ◽  
Vol 13 ◽  
Author(s):  
Rahul Dixit ◽  
Amita Nandal ◽  
Arvind Dhaka ◽  
Vardan Agarwal ◽  
Yohan Varghese
Keyword(s):  
Wavelet Transform ◽  
Singular Value Decomposition ◽  
Discrete Cosine Transform ◽  
Image Watermarking ◽  
Singular Value ◽  
Cover Image ◽  
Lifting Wavelet Transform ◽  
Cosine Transform ◽  
Lifting Wavelet ◽  
Value Decomposition

Background: Nowadays information security is one of the biggest issues of social networks. The multimedia data can be tampered with, and the attackers can then claim its ownership. Image watermarking is a technique that is used for copyright protection and authentication of multimedia. Objective: We aim to create a new and more robust image watermarking technique to prevent illegal copying, editing and distribution of media. Method : The watermarking technique proposed in this paper is non-blind and employs Lifting Wavelet Transform on the cover image to decompose the image into four coefficient matrices. Then Discrete Cosine Transform is applied which separates a selected coefficient matrix into different frequencies and later Singular Value Decomposition is applied. Singular Value Decomposition is also applied to the watermarking image and it is added to the singular matrix of the cover image which is then normalized followed by the inverse Singular Value Decomposition, inverse Discrete Cosine Transform and inverse Lifting Wavelet Transform respectively to obtain an embedded image. Normalization is proposed as an alternative to the traditional scaling factor. Results: Our technique is tested against attacks like rotation, resizing, cropping, noise addition and filtering. The performance comparison is evaluated based on Peak Signal to Noise Ratio, Structural Similarity Index Measure, and Normalized Cross-Correlation. Conclusion: The experimental results prove that the proposed method performs better than other state-of-the-art techniques and can be used to protect multimedia ownership.

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