• DocumentCode
    1797712
  • Title

    Structured sparse coding method for infrared small target detection in video sequence

  • Author

    Chunwei Yang ; Huaping Liu ; Shouyi Liao ; Shicheng Wang

  • Author_Institution
    High-Tech Inst. of Xi´an, Xi´an, China
  • fYear
    2014
  • fDate
    6-11 July 2014
  • Firstpage
    1179
  • Lastpage
    1184
  • Abstract
    In this paper, the infrared small target detection in video sequence is investigated. A collaborative structured sparse coding model which incorporates the L1,2 and L2,1 regularization terms is proposed to detect the infrared small target in video sequence. Further, online dictionary learning is embedded into the model and temporal information is incorporated to eliminate the clutters and noises. Finally, four simulation datasets are constructed to test the proposed method and the experimental validation shows promising results.
  • Keywords
    image coding; image sequences; infrared imaging; learning (artificial intelligence); object detection; L1,2 regularization terms; L2,1 regularization terms; collaborative structured sparse coding model; infrared small target detection; online dictionary learning; video sequence; Dictionaries; Noise; Object detection; Optimization; Robustness; Thyristors; Video sequences;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks (IJCNN), 2014 International Joint Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4799-6627-1
  • Type

    conf

  • DOI
    10.1109/IJCNN.2014.6889584
  • Filename
    6889584
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1797712