An infrared small target detection framework based on local contrast method

作者：Cui, Zheng; Yang, Jingli^*; Li, Junbao; Jiang, Shouda

来源：Measurement, 2016, 91: 405-413.

DOI：10.1016/j.measurement.2016.05.071

• Small target detection
• Modulation map
• Human visual system
• High speed local contrast method
• Machine learning

Small-target detection in infrared imagery used in forward looking infrared is an important task in remote sensing fields. It is important to improve the detection capabilities such as detection rate, false alarm rate and speed. In this letter, a novel approach inspired by human visual system (HVS) is presented. First, block compressed sampling theory was used to compress the image and obtain the modulation map. Then, small abnormal regions in the modulation map were detected by high speed local contrast method and defined as candidate targets. Experimental results show the proposed algorithm pursue good performance in detection rate, false alarm rate and speed simultaneously.

• 出版日期2016-9
• 单位哈尔滨工业大学