We propose a method based on the Poynting vector that combines angle-domain imaging and image amplitude correction to overcome the shortcomings of reverse-time migration that cannot handle different angles during wave...We propose a method based on the Poynting vector that combines angle-domain imaging and image amplitude correction to overcome the shortcomings of reverse-time migration that cannot handle different angles during wave propagation. First, the local image matrix （LIM） and local illumination matrix are constructed, and the wavefield propagation directions are decomposed. The angle-domain imaging conditions are established in the local imaging matrix to remove low-wavenumber artifacts. Next, the angle-domain common image gathers are extracted and the dip angle is calculated, and the amplitude-corrected factors in the dip angle domain are calculated. The partial images are corrected by factors corresponding to the different angles and then are superimposed to perform the amplitude correction of the final image. Angle-domain imaging based on the Poynting vector improves the computation efficiency compared with local plane-wave decomposition. Finally, numerical simulations based on the SEG/EAGE velocity model are used to validate the proposed method.展开更多
In order to solve the problem caused by variation illumination in human face recognition,we bring forward a face recognition algorithm based on the improved multi-sample. In this algorithm,the face image is processed ...In order to solve the problem caused by variation illumination in human face recognition,we bring forward a face recognition algorithm based on the improved multi-sample. In this algorithm,the face image is processed with Retinex theory,meanwhile,the Gabor filter is adopted to perform the feature extraction. The experimental results show that the application of Retinex theory improves the recognition accuracy,and makes the algorithm more robust to the variation illumination. The Gabor filter is more effective and accurate for extracting more useable facial local features. It is proved that the proposed algorithm has good recognition accuracy and it is stable under variation illumination.展开更多
基金sponsored by the Natural Science Fund of Heilongjiang Province(No.F201404)
文摘We propose a method based on the Poynting vector that combines angle-domain imaging and image amplitude correction to overcome the shortcomings of reverse-time migration that cannot handle different angles during wave propagation. First, the local image matrix （LIM） and local illumination matrix are constructed, and the wavefield propagation directions are decomposed. The angle-domain imaging conditions are established in the local imaging matrix to remove low-wavenumber artifacts. Next, the angle-domain common image gathers are extracted and the dip angle is calculated, and the amplitude-corrected factors in the dip angle domain are calculated. The partial images are corrected by factors corresponding to the different angles and then are superimposed to perform the amplitude correction of the final image. Angle-domain imaging based on the Poynting vector improves the computation efficiency compared with local plane-wave decomposition. Finally, numerical simulations based on the SEG/EAGE velocity model are used to validate the proposed method.
基金Sponsored by the Science and Technology Research Projects in Office of Education in Heilongjiang Province(Grant No. 11531034)the Natural Science Fund in Heilongjiang Province(Grant No. F2007-13)the Heilongjiang Postdoctoral Science Foundation (Grant No. LBH-Z06054)
文摘In order to solve the problem caused by variation illumination in human face recognition,we bring forward a face recognition algorithm based on the improved multi-sample. In this algorithm,the face image is processed with Retinex theory,meanwhile,the Gabor filter is adopted to perform the feature extraction. The experimental results show that the application of Retinex theory improves the recognition accuracy,and makes the algorithm more robust to the variation illumination. The Gabor filter is more effective and accurate for extracting more useable facial local features. It is proved that the proposed algorithm has good recognition accuracy and it is stable under variation illumination.
