In order to protect copyright of digital images,a new robust digital image watermarking algorithm based on chaotic system and QR factorization was proposed.The host images were firstly divided into blocks with same si...In order to protect copyright of digital images,a new robust digital image watermarking algorithm based on chaotic system and QR factorization was proposed.The host images were firstly divided into blocks with same size,then QR factorization was performed on each block.Pseudorandom circular chain(PCC) generated by logistic mapping(LM) was applied to select the embedding blocks for enhancing the security of the scheme.The first column coefficients in Q matrix of chosen blocks were modified to embed watermarks without causing noticeable artifacts.Watermark extraction procedure was performed without the original cover image.The experimental results demonstrate that the watermarked images have good visual quality and this scheme is better than the existing techniques,especially when the image is attacked by cropping,noise pollution and so on.Analysis and discussion on robustness and security issues were also presented.展开更多
We present a numerical method for solving the indefinite least squares problem. We first normalize the coefficient matrix. Then we compute the hyperbolic QR factorization of the normalized matrix. Finally we compute t...We present a numerical method for solving the indefinite least squares problem. We first normalize the coefficient matrix. Then we compute the hyperbolic QR factorization of the normalized matrix. Finally we compute the solution by solving several triangular systems. We give the first order error analysis to show that the method is backward stable. The method is more efficient than the backward stable method proposed by Chandrasekaran, Gu and Sayed.展开更多
We propose a robust digital watermarking algorithm for copyright protection.A stable feature is obtained by utilizing QR factorization and discrete cosine transform(DCT) techniques,and a meaningful watermark image is ...We propose a robust digital watermarking algorithm for copyright protection.A stable feature is obtained by utilizing QR factorization and discrete cosine transform(DCT) techniques,and a meaningful watermark image is embedded into an image by modifying the stable feature with a quantization index modulation(QIM) method.The combination of QR factorization,DCT,and QIM techniques guarantees the robustness of the algorithm.Furthermore,an embedding location selection method is exploited to select blocks with small modifications as the embedding locations.This can minimize the embedding distortion and greatly improve the imperceptibility of our scheme.Several standard images were tested and the experimental results were compared with those of other published schemes.The results demonstrate that our proposed scheme can achieve not only better imperceptibility,but also stronger robustness against common signal processing operations and lossy compressions,such as filtering,noise addition,scaling,sharpening,rotation,cropping,and JPEG/JPEG2000 compression.展开更多
This paper considers the updating problem of the hyperbolic matrix factorizations. The sufficient conditions for the existence of the updated hyperbolic matrix factorizations are first provided. Then, some differentia...This paper considers the updating problem of the hyperbolic matrix factorizations. The sufficient conditions for the existence of the updated hyperbolic matrix factorizations are first provided. Then, some differential inequalities and first order perturbation expansions for the updated hyperbolic factors are derived. These results generalize the corresponding ones for the updating problem of the classical QR factorization obtained by Jiguang SUN.展开更多
Complete temperature field estimation from limited local measurements is widely desired in many industrial and scientific applications of thermal engineering. Since the sensor configuration dominates the reconstructio...Complete temperature field estimation from limited local measurements is widely desired in many industrial and scientific applications of thermal engineering. Since the sensor configuration dominates the reconstruction performance, some progress has been made in designing sensor placement methods. But these approaches remain to be improved in terms of both accuracy and efficiency due to the lack of comprehensive schemes and efficient optimization algorithms. In this work, we develop a datadriven sensor placement framework for thermal field reconstruction. Specifically, we first tailor the low-dimensional model from the prior thermal maps to represent the high-dimensional temperature distribution states by virtue of proper orthogonal decomposition technique. Then, on such subspace, a recursive greedy algorithm with determinant maximization as the objective function is developed to optimize the sensor placement configuration. Furthermore, we find that the same sensor configuration can be yielded faster by the standard procedures of column-pivoted QR factorization, which allows concise software implementation with readily available function packages. When the sensor locations are determined, we advocate using the databased closed-form estimator to minimize the reconstruction error. Real-time thermal monitoring on the multi-core processor is employed as the case to demonstrate the effectiveness of the proposed methods for thermal field reconstruction. Extensive evaluations are conducted on simulation or experimental datasets of three processors with different architectures. The results show that our method achieves state-of-the-art reconstruction performance while possessing the lowest computational complexity when compared with the existing methods.展开更多
基金Project(2007AA01Z241-2) supported by the National High-tech Research and Development Program of ChinaProject(2006XM002) supported by Beijing Jiaotong University Science Foundation,ChinaProject(0910KYZY55) supported by the Fundamental Research Funds for the Central University in China
文摘In order to protect copyright of digital images,a new robust digital image watermarking algorithm based on chaotic system and QR factorization was proposed.The host images were firstly divided into blocks with same size,then QR factorization was performed on each block.Pseudorandom circular chain(PCC) generated by logistic mapping(LM) was applied to select the embedding blocks for enhancing the security of the scheme.The first column coefficients in Q matrix of chosen blocks were modified to embed watermarks without causing noticeable artifacts.Watermark extraction procedure was performed without the original cover image.The experimental results demonstrate that the watermarked images have good visual quality and this scheme is better than the existing techniques,especially when the image is attacked by cropping,noise pollution and so on.Analysis and discussion on robustness and security issues were also presented.
文摘We present a numerical method for solving the indefinite least squares problem. We first normalize the coefficient matrix. Then we compute the hyperbolic QR factorization of the normalized matrix. Finally we compute the solution by solving several triangular systems. We give the first order error analysis to show that the method is backward stable. The method is more efficient than the backward stable method proposed by Chandrasekaran, Gu and Sayed.
基金Project supported by the "Shuang Bai Plan" and "Shenzhen-Hong Kong Innovation Circle" Research Program of Shenzhen,China
文摘We propose a robust digital watermarking algorithm for copyright protection.A stable feature is obtained by utilizing QR factorization and discrete cosine transform(DCT) techniques,and a meaningful watermark image is embedded into an image by modifying the stable feature with a quantization index modulation(QIM) method.The combination of QR factorization,DCT,and QIM techniques guarantees the robustness of the algorithm.Furthermore,an embedding location selection method is exploited to select blocks with small modifications as the embedding locations.This can minimize the embedding distortion and greatly improve the imperceptibility of our scheme.Several standard images were tested and the experimental results were compared with those of other published schemes.The results demonstrate that our proposed scheme can achieve not only better imperceptibility,but also stronger robustness against common signal processing operations and lossy compressions,such as filtering,noise addition,scaling,sharpening,rotation,cropping,and JPEG/JPEG2000 compression.
基金Supported by the National Natural Science Foundation of China(Grant Nos.1120150711171361)the Natural Science Foundation Project of CQ CSTC(Grant No.2010BB9215)
文摘This paper considers the updating problem of the hyperbolic matrix factorizations. The sufficient conditions for the existence of the updated hyperbolic matrix factorizations are first provided. Then, some differential inequalities and first order perturbation expansions for the updated hyperbolic factors are derived. These results generalize the corresponding ones for the updating problem of the classical QR factorization obtained by Jiguang SUN.
基金This work was supported by the Foundation for Innovative Research Groups of the National Natural Science Foundation of China(Grant No.51521004)。
文摘Complete temperature field estimation from limited local measurements is widely desired in many industrial and scientific applications of thermal engineering. Since the sensor configuration dominates the reconstruction performance, some progress has been made in designing sensor placement methods. But these approaches remain to be improved in terms of both accuracy and efficiency due to the lack of comprehensive schemes and efficient optimization algorithms. In this work, we develop a datadriven sensor placement framework for thermal field reconstruction. Specifically, we first tailor the low-dimensional model from the prior thermal maps to represent the high-dimensional temperature distribution states by virtue of proper orthogonal decomposition technique. Then, on such subspace, a recursive greedy algorithm with determinant maximization as the objective function is developed to optimize the sensor placement configuration. Furthermore, we find that the same sensor configuration can be yielded faster by the standard procedures of column-pivoted QR factorization, which allows concise software implementation with readily available function packages. When the sensor locations are determined, we advocate using the databased closed-form estimator to minimize the reconstruction error. Real-time thermal monitoring on the multi-core processor is employed as the case to demonstrate the effectiveness of the proposed methods for thermal field reconstruction. Extensive evaluations are conducted on simulation or experimental datasets of three processors with different architectures. The results show that our method achieves state-of-the-art reconstruction performance while possessing the lowest computational complexity when compared with the existing methods.
