| 1 | Collaborative representation with background purification and saliency weight for hyperspectral anomaly detection显示文摘Collaborative representation-based detection(CRD)has been developed in hyperspectral anomaly detection tasks and testified to be very effective;however,heterogeneous pixels in the background may affect the accuracy of linear representation and make its performance suboptimal.To address this issue,a background purification framework based on linear representation is proposed,in which an automatic outlier removal strategy based on initial coefficients is designed to purify the background.In the proposed method,the classic least squares technique is firstly adopted to obtain preliminary linear representation coefficients,which are positively correlated with its contribution to a central testing pixel.Then,using statistical analysis of the representation coefficients,purified background pixels are obtained.Furthermore,a saliency weight is applied to fully utilize the spatial information of inner window pixels.Extensive experiments with three real hyperspectral datasets show that the proposed method outperforms state-of-the-art CRD and other traditional detectors. | Zengfu HOU Wei LI Ran TAO Pengge MA Weihua SHI | 2022 | Science China(Information Sciences)2022，65，1： | 1 |
| 2 | Improved Weighted Local Contrast Method for Infrared Small Target Detection显示文摘In order to address the problem of high false alarm rate and low probabilities of infrared small target detection in complex low-altitude background,an infrared small target detection method based on improved weighted local contrast is proposed in this paper.First,the ratio information between the target and local background is utilized as an enhancement factor.The local contrast is calculated by incorporating the heterogeneity between the target and local background.Then,a local product weighted method is designed based on the spatial dissimilarity between target and background to further enhance target while suppressing background.Finally,the location of target is obtained by adaptive threshold segmentation.As experimental results demonstrate,the method shows superior performance in several evaluation metrics compared with six existing algorithms on different datasets containing targets such as unmanned aerial vehicles(UAV). | Pengge Ma Jiangnan Wang Dongdong Pang Tao Shan Junling Sun Qiuchun Jin | 2024 | Journal of Beijing Institute of Technology2024，33，1： | 0 |
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