Since the 1990s, information hiding technology has become a major research focus in the field of information technology. The purpose of information hiding is to embed hidden data in digital media, such as image, audio, video, and so on. With the development of related technologies, information hiding has become an independent discipline, and its coverage is also expanding. According to the purpose of hiding information and technical requirements, invisibility, robustness, undetectability, security [1
], and other attributes are all distinctive features of information hiding technology.
As digital media can be easily copied, altered, and illegally distributed, copyright protection of digital media has aroused increasingly widespread attention. How to protect the integrity and authenticity of digital media becomes urgent and important. Thus, digital signature [2
] and digital watermarking [3
] have been proposed for data hiding to solve this problem. Due to its superior performance, digital watermarking is applied as an effective method to solve the image’s copyright issue. According to different functions, digital watermarking can be classified into three types, containing robust watermarking, fragile watermarking, and semi-fragile watermarking. Robust watermarking can resist all kinds of attacks and common processing, which is applied for copyright protection. Fragile watermarking is sensitive to attacks, including malicious tampering and common processing. Combining advantages of the two above watermarking methods, semi-fragile watermarking is proposed to distinguish malicious tampering from non-malicious modification with the certain ability of resisting common processing. According to the domain where the watermark is embedded, two types of digital watermarking techniques can be defined [4
]: spatial domain watermarking [6
], and frequency or transform domain watermarking [7
]. Spatial domain methods modify the pixel value of the digital image directly to embed the watermark. The least significant bit (LSB) algorithm is the common and simplest algorithm applied in spatial watermarking schemes [8
], embedding the watermark information into the LSB or multiple bit layers. Correspondingly, frequency domain methods embed the watermark information by modifying transform coefficients of the original image. Compared with spatial methods, schemes based on transforms have better imperceptibility and robustness. Discrete cosine transform (DCT), discrete wavelet transform (DWT), discrete sine transform (DST), and singular value decomposition (SVD) [9
] are common transforms applied in frequency domain watermarking. Moreover, other special transforms, such as redundant DWT (RDWT) [10
], fractional wavelet transform (FWT) [11
], and QR decomposition [12
], can be applied for better performance in some certain aspects. In recent years, these transforms are still applied widely in the watermarking field. For example, Rasti et al. [12
] proposed a robust color video watermarking scheme based on QR decomposition and entropy analysis, embedding the watermark into the block selected by entropy analysis. The selected block is performed by DWT, Chirp-Z transform (CZT), QR decomposition, and SVD for watermark embedding. In [13
], Cheng et al. proposed a robust watermarking with the combination of DWT and DCT. In the embedding process, the HL2
sub-band coefficient is divided into 4 × 4 blocks after decomposing the cover image by two-level DWT. Then, the DCT is performed for each block. According to the watermark bit, two pseudo-random sequences are embedded into the middle band coefficients of DCT. Besides, Guo et al. [14
] proposed a robust watermarking scheme based on DCT and DWT in the encrypted domain to improve the robustness, using an image splitting method to embed the watermark in the low-middle frequency coefficients. Nguyen et al. [15
] proposed a fragile watermarking for image authentication in the wavelet domain, where the authentication code is embedded into the two-level low frequency sub-band. In [16
], Martino and Sessa introduced a fragile watermarking tampering detection with compressed images based on a fuzzy transform, which is applied to compress each block. Besides, fuzzy c-means clustering technique is proposed to form the relationship between image blocks, and this method achieves more accurate tampering detection and localization. Lin and Tsay [17
] presented a passive approach for tampering detection and location in video sequences with camera motion, which is based on spatio-temporal coherence analysis.
The scale-invariant feature transform (SIFT) [18
] is a classical algorithm for interest points detection, as well as local features description, which has three advantages: (1) the number of extracted feature points or keypoints is significant with appropriate parameter settings; (2) the image feature extracted by SIFT has great uniqueness for accurate matching; and (3) SIFT features have better invariance ability on rotation, scaling, and translation. Owing to its efficiency [19
], SIFT algorithm is widely used in the field of image processing to match two images, locate the position, and recognize objects. Moreover, SIFT provides good performance of watermarking schemes in recent years. Lee et al. [20
] firstly proposed a novel image watermarking scheme using local invariant features, and embedded the watermark into circular patches generated by SIFT. In [21
], Lyu et al. proposed an image watermarking scheme based on SIFT and DWT, and applied the DWT on the selected SIFT areas. Thorat and Jadhav [22
] proposed an anti-geometric attack watermarking scheme based on integer wavelet transform (IWT) and SIFT, where feature points in red components of the image are extracted by SIFT, and blue and green components are performed by IWT to extract low frequency coefficients for watermark embedding. Luo et al. [23
] presented an adaptive robust watermarking scheme based on discrete Fourier transform (DFT) and SIFT to deal with the synchronization errors. Pham et al. [24
] proposed a robust SIFT and DCT-based watermarking scheme, embedding the watermark into the selected feature regions after DCT. In [25
], Zhang and Tang introduced an SVD and SIFT-based watermarking algorithm to solve the synchronization problem, where SIFT is used for watermarking resynchronization.
Owing to the robustness feature of SIFT and SVD, as well as better concentration of all phase biorthogonal transform (APBT) in low frequencies, we propose the idea of combining local digital watermarking with SIFT, SVD, and APBT, and make comparisons between previous watermarking schemes and the proposed watermarking algorithm in this paper. The purpose of this paper is to propose a robust watermarking algorithm with better imperceptibility and stronger robustness for copyright protection.