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
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;
Conference_Titel :
Neural Networks (IJCNN), 2014 International Joint Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4799-6627-1
DOI :
10.1109/IJCNN.2014.6889584
