| Citation: |
YANG Chunwei, WANG Shicheng, LIAO Shouyi, LIU Huaping. Forward-looking-infrared Building Object Tracking Based on Sparse Representation of Covariance Descriptor[J]. Infrared Technology , 2016, 38(5): 389-395.
|
| [1] | CAO Min, WANG Yao. Typical Infrared Object Segmentation Based on Sparse Shape Prior and Variational Regularization[J]. Infrared Technology , 2025, 47(5): 611-618. |
| [2] | WU Lingxiao, KANG Jiayin, JI Yunxiang. Infrared and Visible Image Fusion Based on Guided Filter and Sparse Representation in NSST Domain[J]. Infrared Technology , 2023, 45(9): 915-924. |
| [3] | LIAO Jiajun, LIU Zhigang, JIANG Jiangjun, LU Zhiyong. Target Detection in Hyperspectral Image Using Two Steps Reconstruction Based on Sparse Representation[J]. Infrared Technology , 2016, 38(8): 699-704. |
| [4] | YANG Chunwei, WANG Shicheng, LIAO Shouyi, LIU Huaping. An Infrared Target Recognition Method Based on Kernel Sparse Coding[J]. Infrared Technology , 2016, 38(3): 230-235. |
| [5] | MEI Jiacheng, WANG Rui, YE Hanmin. Compressive Fusion and Target Detection Based on Sparse Representation[J]. Infrared Technology , 2016, 38(3): 218-224. |
| [6] | ZOU Hui, HUANG Fuzhen. Infrared Image Segmentation for Electrical Equipment Based on FAsT-Match Algorithm[J]. Infrared Technology , 2016, 38(1): 21-27. |
| [7] | WANG Zhi-she, YANG Feng-bao, PENG Zhi-hao. Multi-source Heterogeneous Image Fusion Based on NSST and Sparse Presentation[J]. Infrared Technology , 2015, (3): 210-217. |
| [8] | SUN Jun-ding, ZHAO Hui-hui. Sparse Representation and Applications in Image Processing[J]. Infrared Technology , 2014, (7): 533-537. |
| [9] | LI Wei, SHEN Zhen-kang, LI Biao. Solving Parameters of Affine Transformation Based on ACO[J]. Infrared Technology , 2007, 29(11): 662-665. DOI: 10.3969/j.issn.1001-8891.2007.11.011 |
| [10] | ZHAO Qin, ZHOU Tao, SHU Qin. Discussion of Image Registration Based on Feature Points[J]. Infrared Technology , 2006, 28(6): 327-330. DOI: 10.3969/j.issn.1001-8891.2006.06.005 |
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