In this paper,an efficient algorithm is proposed for Toeplitz matrix recovery via hybrid thresh-olding operator.The algorithm is based on the mean-value augmented Lagrangian multiplier algorithm and the singular value...In this paper,an efficient algorithm is proposed for Toeplitz matrix recovery via hybrid thresh-olding operator.The algorithm is based on the mean-value augmented Lagrangian multiplier algorithm and the singular values processed by hybrid singular value threshold operator.The new algorithm ensures that the matrix generated by the iteration has a Toeplitz structure,which reduces the calculation time and obtains a more accurate Toeplitz matrix.The convergence of the new algorithm is discussed under certain assumptions.Numerical experiments show that the new algorithm achieves less CPU time than the mean-value augmented Lagrangian multiplier algorithm,smooth augmented Lagrangian multiplier algorithm,and augmented Lagrangian multiplier algorithm.展开更多
Homologous feature point extraction is a key problem in the optical and synthetic aperture radar （SAR） image registration for islands. A new feature point extraction method using a threshold shrink operator and non-...Homologous feature point extraction is a key problem in the optical and synthetic aperture radar （SAR） image registration for islands. A new feature point extraction method using a threshold shrink operator and non-subsampled wavelet transform （TSO-NSWT） for optical and SAR image registration was proposed. Moreover, the matching for this proposed feature was different from the traditional feature matching strategies and was performed using a similarity measure computed from neighborhood circles in low-frequency bands. Then, a number of reliably matched couples with even distributions were obtained, which assured the accuracy of the registration. Application of the proposed algorithm to SPOT-5 （multi-spectral） and YG-1 （SAR） images showed that a large number of accurately matched couples could be identified. Additionally, both of the root mean square error （RMSE） patterns of the registration parameters computed based on the TSO-NSWT algorithm and traditional NSWT algorithm were analyzed and compared, which further demonstrated the effectiveness of the proposed algorithm. The algorithm can supply the crucial step for island image registration and island recognition.展开更多
基金supported by National Natural Science Foundation of China(No.12371381)the special fund for Science and Technology Innovation Team of Shanxi Province(No.202204051002018)。
文摘In this paper,an efficient algorithm is proposed for Toeplitz matrix recovery via hybrid thresh-olding operator.The algorithm is based on the mean-value augmented Lagrangian multiplier algorithm and the singular values processed by hybrid singular value threshold operator.The new algorithm ensures that the matrix generated by the iteration has a Toeplitz structure,which reduces the calculation time and obtains a more accurate Toeplitz matrix.The convergence of the new algorithm is discussed under certain assumptions.Numerical experiments show that the new algorithm achieves less CPU time than the mean-value augmented Lagrangian multiplier algorithm,smooth augmented Lagrangian multiplier algorithm,and augmented Lagrangian multiplier algorithm.
基金The National Natural Science Foundation of China under contract No.41271409the National Key Technology Research and Development Program under contract No.2011BAH23B00the National High Technology Research and Development Program(863 Program)of China under contract No.2012AA12A406
文摘Homologous feature point extraction is a key problem in the optical and synthetic aperture radar （SAR） image registration for islands. A new feature point extraction method using a threshold shrink operator and non-subsampled wavelet transform （TSO-NSWT） for optical and SAR image registration was proposed. Moreover, the matching for this proposed feature was different from the traditional feature matching strategies and was performed using a similarity measure computed from neighborhood circles in low-frequency bands. Then, a number of reliably matched couples with even distributions were obtained, which assured the accuracy of the registration. Application of the proposed algorithm to SPOT-5 （multi-spectral） and YG-1 （SAR） images showed that a large number of accurately matched couples could be identified. Additionally, both of the root mean square error （RMSE） patterns of the registration parameters computed based on the TSO-NSWT algorithm and traditional NSWT algorithm were analyzed and compared, which further demonstrated the effectiveness of the proposed algorithm. The algorithm can supply the crucial step for island image registration and island recognition.
