Contraposing the need of the robust digital watermark for the copyright protection field, a new digital watermarking algorithm in the non-subsampled contourlet transform （NSCT） domain is proposed. The largest energy...Contraposing the need of the robust digital watermark for the copyright protection field, a new digital watermarking algorithm in the non-subsampled contourlet transform （NSCT） domain is proposed. The largest energy sub-band after NSCT is selected to embed watermark. The watermark is embedded into scaleinvariant feature transform （SIFT） regions. During embedding, the initial region is divided into some cirque sub-regions with the same area, and each watermark bit is embedded into one sub-region. Extensive simulation results and comparisons show that the algorithm gets a good trade-off of invisibility, robustness and capacity, thus obtaining good quality of the image while being able to effectively resist common image processing, and geometric and combo attacks, and normalized similarity is almost all reached.展开更多
A new spectral matching algorithm is proposed by us- ing nonsubsampled contourlet transform and scale-invariant fea- ture transform. The nonsubsampled contourlet transform is used to decompose an image into a low freq...A new spectral matching algorithm is proposed by us- ing nonsubsampled contourlet transform and scale-invariant fea- ture transform. The nonsubsampled contourlet transform is used to decompose an image into a low frequency image and several high frequency images, and the scale-invariant feature transform is employed to extract feature points from the low frequency im- age. A proximity matrix is constructed for the feature points of two related images. By singular value decomposition of the proximity matrix, a matching matrix （or matching result） reflecting the match- ing degree among feature points is obtained. Experimental results indicate that the proposed algorithm can reduce time complexity and possess a higher accuracy.展开更多
In this paper, we proposed a registration method by combining the morphological component analysis(MCA) and scale-invariant feature transform(SIFT) algorithm. This method uses the perception dictionaries,and combines ...In this paper, we proposed a registration method by combining the morphological component analysis(MCA) and scale-invariant feature transform(SIFT) algorithm. This method uses the perception dictionaries,and combines the Basis-Pursuit algorithm and the Total-Variation regularization scheme to extract the cartoon part containing basic geometrical information from the original image, and is stable and unsusceptible to noise interference. Then a smaller number of the distinctive key points will be obtained by using the SIFT algorithm based on the cartoon part of the original image. Matching the key points by the constrained Euclidean distance,we will obtain a more correct and robust matching result. The experimental results show that the geometrical transform parameters inferred by the matched key points based on MCA+SIFT registration method are more exact than the ones based on the direct SIFT algorithm.展开更多
Phase space can be constructed for N equal and distinguishable binary subsystems which are correlated in a scale-invariant manner. In the paper, correlation coefficient and reduced probability are introduced to charac...Phase space can be constructed for N equal and distinguishable binary subsystems which are correlated in a scale-invariant manner. In the paper, correlation coefficient and reduced probability are introduced to characterize the scale-invariant correlated binary subsystems. Probabilistic sets for the correlated binary subsystems satisfy Leibnitz triangle rule in the sense that the marginal probabilities of N-system are equal to the joint probabilities of the （N - 1）-system. For entropic index q ≠ 1, nonextensive entropy Sq is shown to be additive in the scale-invariant occupation of phase space.展开更多
基金supported by the National Natural Science Foundation of China(61379010)the Natural Science Basic Research Plan in Shaanxi Province of China(2015JM6293)
文摘Contraposing the need of the robust digital watermark for the copyright protection field, a new digital watermarking algorithm in the non-subsampled contourlet transform （NSCT） domain is proposed. The largest energy sub-band after NSCT is selected to embed watermark. The watermark is embedded into scaleinvariant feature transform （SIFT） regions. During embedding, the initial region is divided into some cirque sub-regions with the same area, and each watermark bit is embedded into one sub-region. Extensive simulation results and comparisons show that the algorithm gets a good trade-off of invisibility, robustness and capacity, thus obtaining good quality of the image while being able to effectively resist common image processing, and geometric and combo attacks, and normalized similarity is almost all reached.
基金supported by the National Natural Science Foundation of China (6117212711071002)+1 种基金the Specialized Research Fund for the Doctoral Program of Higher Education (20113401110006)the Innovative Research Team of 211 Project in Anhui University (KJTD007A)
文摘A new spectral matching algorithm is proposed by us- ing nonsubsampled contourlet transform and scale-invariant fea- ture transform. The nonsubsampled contourlet transform is used to decompose an image into a low frequency image and several high frequency images, and the scale-invariant feature transform is employed to extract feature points from the low frequency im- age. A proximity matrix is constructed for the feature points of two related images. By singular value decomposition of the proximity matrix, a matching matrix （or matching result） reflecting the match- ing degree among feature points is obtained. Experimental results indicate that the proposed algorithm can reduce time complexity and possess a higher accuracy.
基金the National Science Foundation of China(No.61471185)the Natural Science Foundation of Shandong Province(No.ZR2016FM21)+1 种基金Shandong Province Science and Technology Plan Project(No.2015GSF116001)Yantai City Key Research and Development Plan Project(Nos.2014ZH157 and2016ZH057)
文摘In this paper, we proposed a registration method by combining the morphological component analysis(MCA) and scale-invariant feature transform(SIFT) algorithm. This method uses the perception dictionaries,and combines the Basis-Pursuit algorithm and the Total-Variation regularization scheme to extract the cartoon part containing basic geometrical information from the original image, and is stable and unsusceptible to noise interference. Then a smaller number of the distinctive key points will be obtained by using the SIFT algorithm based on the cartoon part of the original image. Matching the key points by the constrained Euclidean distance,we will obtain a more correct and robust matching result. The experimental results show that the geometrical transform parameters inferred by the matched key points based on MCA+SIFT registration method are more exact than the ones based on the direct SIFT algorithm.
基金the National Natural Science Foundation of China(No.60474069)
文摘Phase space can be constructed for N equal and distinguishable binary subsystems which are correlated in a scale-invariant manner. In the paper, correlation coefficient and reduced probability are introduced to characterize the scale-invariant correlated binary subsystems. Probabilistic sets for the correlated binary subsystems satisfy Leibnitz triangle rule in the sense that the marginal probabilities of N-system are equal to the joint probabilities of the （N - 1）-system. For entropic index q ≠ 1, nonextensive entropy Sq is shown to be additive in the scale-invariant occupation of phase space.
