# RST Resilient Watermarking Scheme Based on DWT-SVD and Scale-Invariant Feature Transform
## 1 Introduction  
With the tremendous growth in information industry recently, as one of the most essential methods to convey the information from one side to the other, digital images can be easily tampered, which can consequently result in security problems with copyright issues. Thus, the scheme for the authenticity and integrity of image protection becomes essential and meaningful. To solve this problem, digital signatures [1; 2] and digital image watermarking [3] are proposed. Because digital signatures can only estimate whether images are tampered but cannot locate the tampered region, the watermarking technique, an effective method to solve the copyright problem of image content, is proposed. According to different characters, watermarking can be classified into three categories: (i) robust watermarking used for copyright protection, which can resist all kinds of attacks; (ii) fragile watermarking, which is sensitive to attacks including malicious tampering and common processing; and (iii) semi-fragile watermarking used to distinguish malicious tampering from non-malicious modification, which is a combination of advantages of robust and fragile watermarking. In addition, both fragile watermarking methods and semi-fragile watermarking methods can be applied in image tamper, location, and recovery. From the perspective of the working domain where the watermark is embedded, this effective technique can be divided into spatial domain and transform domain [4]. The spatial domain methods modify the pixel value of the digital image directly to embed the watermark information. The advantages of spatial watermarking method are easy implementation and low computational complexity. However, this kind of method is fragile to the common image processing operation and other attacks. In contrast, the watermark information is embedded into the host image by modifying transform coefficients of the original image in the transform domain methods. Compared with spatialmethods, methods based on mathematical transform have better imperceptibility and robustness. Discrete cosine transform (DCT), discrete wavelet transform (DWT), discrete Fourier transform (DFT), and singular value decomposition (SVD) [5] are the common transforms applied in the transform domain watermarking. Owing to its stable algebraic character, SVD is applied as a normal method for watermarking scheme, especially for robust watermarking. [PERSON] and [PERSON] [6] firstly introduced the typical watermarking algorithm based on SVD. In this method, singular values obtained by SVD are modified for the purpose of embedding the watermarking into the host image. In the watermark embedding process, the watermark information is embedded in the form of weighted sum with the help of the scale factors. Different from [PERSON] and [PERSON]'s scheme, [PERSON] et al. [7] proposed another SVD based watermarking scheme, where the watermark is embedded by substituting the specific singular value with the watermark value. In addition, [PERSON] et al. [8] introduced a blind dual color image watermarking scheme based on SVD. By analyzing the orthogonal matrix \(U\) generated from the SVD, a similarity correlation, in which elements in the second row first column and the third row first column have the same sign and high normalized cross-correlation, is found between these two elements, which can be used in watermarking embedding and extraction. [PERSON] et al. [9] proposed quantized SVD (QSVD) based blind watermarking method, which realized embedding of the watermark by modifying the quaternion elements in \(U\) matrix. Worthy of mention is the quaternion, a type of hyper-complex number, consists of one real component and three imaginary components, and an image can be encoded into the form of quaternion. To obtain better performance of the watermarking algorithm, some hybrid schemes based on SVD and other transforms have been proposed. In [10], [PERSON] et al. introduced a novel watermarking algorithm based on SVD and DCT.