Ruizhen Liu

Bio: Ruizhen Liu is an academic researcher. The author has contributed to research in topics: Inertial navigation system & Digital watermarking. The author has an hindex of 1, co-authored 1 publications receiving 922 citations.

An SVD-based watermarking scheme for protecting rightful ownership

Abstract: Digital watermarking has been proposed as a solution to the problem of copyright protection of multimedia documents in networked environments. There are two important issues that watermarking algorithms need to address. First, watermarking schemes are required to provide trustworthy evidence for protecting rightful ownership. Second, good watermarking schemes should satisfy the requirement of robustness and resist distortions due to common image manipulations (such as filtering, compression, etc.). In this paper, we propose a novel watermarking algorithm based on singular value decomposition (SVD). Analysis and experimental results show that the new watermarking method performs well in both security and robustness.

Polarized light compass-aided inertial navigation under discontinuous observations environment.

Abstract: In recent years, integrated polarized light/inertial heading measurement systems have been widely used to obtain autonomous heading measurements of small unmanned combat platforms in the case of satellite navigation rejection. However, existing polarized light/inertial heading measurement systems have certain limitations. For example, they can only measure the heading angle in environments where continuous observations can be obtained. When encountering a complex environment with trees and/or tall buildings, the measured heading angle will contain sharp noise which greatly affects its accuracy. In particular, when encountering an underpass, it will lead to the complete loss of lock of the polarized light compass signal. Therefore, for the problem of sharp noise arising from a complex environment, a robust Cubature Kalman filter (CKF) data-fusion algorithm is proposed and verified by experiments. It is proved that the robust CKF algorithm has a certain ability to filter out the effects of poor measurements. After application of the robust CKF algorithm, the Root Mean Square Error (RMSE) of the heading angle reaches 0.3612°. This method solves the problem of low precision and poor stability of the polarized light/inertial system when high buildings and/or trees are contained in a complex environment. Next, in view of the problem that the polarized light compass signal is completely lost due to passing through an underground passage, a random forest regression (RFR) neural network model is established and introduced into the combined system. Simulated and outdoor experiments are carried out to verify the designed model using data obtained with a vehicle. The RMSE of the heading angle obtained in the experiment is 1.1894°, which solves the problem that the polarized light/inertial system cannot utilize discontinuous observations when attempting to detect the carrier heading angle.

Digital Image Watermarking Using Discrete Wavelet Transform and Singular Value Decomposition

Abstract: The main objective of developing an image-watermarking technique is to satisfy both imperceptibility and robustness requirements. To achieve this objective, a hybrid image-watermarking scheme based on discrete wavelet transform (DWT) and singular value decomposition (SVD) is proposed in this paper. In our approach, the watermark is not embedded directly on the wavelet coefficients but rather than on the elements of singular values of the cover image's DWT subbands. Experimental results are provided to illustrate that the proposed approach is able to withstand a variety of image-processing attacks.

Robust DWT-SVD domain image watermarking: embedding data in all frequencies

Abstract: Protection of digital multimedia content has become an increasingly important issue for content owners and service providers. As watermarking is identified as a major technology to achieve copyright protection, the relevant literature includes several distinct approaches for embedding data into a multimedia element (primarily images, audio, and video). Because of its growing popularity, the Discrete Wavelet Transform (DWT) is commonly used in recent watermarking schemes. In a DWT-based scheme, the DWT coefficients are modified with the data that represents the watermark. In this paper, we present a hybrid scheme based on DWT and Singular Value Decomposition (SVD). After decomposing the cover image into four bands, we apply the SVD to each band, and embed the same watermark data by modifying the singular values. Modification in all frequencies allows the development of a watermarking scheme that is robust to a wide range of attacks.

An SVD-based grayscale image quality measure for local and global assessment

Abstract: The important criteria used in subjective evaluation of distorted images include the amount of distortion, the type of distortion, and the distribution of error. An ideal image quality measure should, therefore, be able to mimic the human observer. We present a new grayscale image quality measure that can be used as a graphical or a scalar measure to predict the distortion introduced by a wide range of noise sources. Based on singular value decomposition, it reliably measures the distortion not only within a distortion type at different distortion levels, but also across different distortion types. The measure was applied to five test images (airplane, boat, Goldhill, Lena, and peppers) using six types of distortion (JPEG, JPEG 2000, Gaussian blur, Gaussian noise, sharpening, and DC-shifting), each with five distortion levels. Its performance is compared with PSNR and two recent measures.

Optimized gray-scale image watermarking using DWT-SVD and Firefly Algorithm

Abstract: This paper presents an optimized watermarking scheme based on the discrete wavelet transform (DWT) and singular value decomposition (SVD). The singular values of a binary watermark are embedded in singular values of the LL3 sub-band coefficients of the host image by making use of multiple scaling factors (MSFs). The MSFs are optimized using a newly proposed Firefly Algorithm having an objective function which is a linear combination of imperceptibility and robustness. The PSNR values indicate that the visual quality of the signed and attacked images is good. The embedding algorithm is robust against common image processing operations. It is concluded that the embedding and extraction of the proposed algorithm is well optimized, robust and show an improvement over other similar reported methods.