Robust Principal Component Analysis-Based Infrared Small Target Detection


  • Qiwei Chen Soochow University
  • Cheng Wu Soochow University
  • Yiming Wang Soochow University



A method based on Robust Principle Component Analysis (RPCA) technique is proposed to detect small targets in infrared images. Using the low rank characteristic of background and the sparse characteristic of target, the observed image is regarded as the sum of a low-rank background matrix and a sparse outlier matrix, and then the decomposition is solved by the RPCA. The infrared small target is extracted from the single-frame image or multi-frame sequence. In order to get more efficient algorithm, the iteration process in the augmented Lagrange multiplier method is improved. The simulation results show that the method can detect out the small target precisely and efficiently.




How to Cite

Chen, Q., Wu, C., & Wang, Y. (2019). Robust Principal Component Analysis-Based Infrared Small Target Detection. Proceedings of the AAAI Conference on Artificial Intelligence, 33(01), 9925-9926.



Student Abstract Track