Boolean map saliency combined with motion feature used for dim and small target detection in infrared video sequences

Infrared dim and small target detection plays an important role in infrared search and tracking systems. In this paper, a novel infrared dim and small target detection method based on Boolean map saliency and motion feature is proposed. Infrared targets are the most salient parts in images, with high gray level and continuous moving trajectory. Utilizing this property, we build a feature space containing gray level feature and motion feature. The gray level feature is the intensity of input images, while the motion feature is obtained by motion charge in consecutive frames. In the second step, the Boolean map saliency approach is implemented on the gray level feature and motion feature to obtain the gray saliency map and motion saliency map. In the third step, two saliency maps are combined together to get the final result. Numerical experiments have verified the effectiveness of the proposed method. The final detection result can not only get an accurate detection result, but also with fewer false alarms, which is suitable for practical use.

[1]  Stan Sclaroff,et al.  Saliency Detection: A Boolean Map Approach , 2013, 2013 IEEE International Conference on Computer Vision.

[2]  Jie Ma,et al.  A Robust Directional Saliency-Based Method for Infrared Small-Target Detection Under Various Complex Backgrounds , 2013, IEEE Geoscience and Remote Sensing Letters.

[3]  Yair Barniv,et al.  Dynamic Programming Solution for Detecting Dim Moving Targets , 1985, IEEE Transactions on Aerospace and Electronic Systems.

[4]  Larry B. Stotts,et al.  Optical moving target detection with 3-D matched filtering , 1988 .

[5]  Jie Ma,et al.  Robust method for infrared small-target detection based on Boolean map visual theory. , 2014, Applied optics.

[6]  Jun Huang,et al.  An Infrared Small Target Detecting Algorithm Based on Human Visual System , 2016, IEEE Geoscience and Remote Sensing Letters.

[7]  Fan Fan,et al.  A Robust Infrared Small Target Detection Algorithm Based on Human Visual System , 2014, IEEE Geoscience and Remote Sensing Letters.

[8]  Faliang Chang,et al.  Infrared small target detection algorithm based on feature salience , 2011 .

[9]  Zhonghua Wang,et al.  Motion estimation and spatial-temporal filter-based infrared small target detection algorithm , 2015, Int. J. Wirel. Mob. Comput..

[10]  Robert W. Fries,et al.  Three Dimensional Matched Filtering , 1989, Photonics West - Lasers and Applications in Science and Engineering.

[11]  Rongrong Ji,et al.  Robust infrared target tracking based on particle filter with embedded saliency detection , 2015, Inf. Sci..

[12]  Vikram Krishnamurthy,et al.  Performance analysis of a dynamic programming track before detect algorithm , 2002 .

[13]  Antonio Fernández-Caballero,et al.  Motion features to enhance scene segmentation in active visual attention , 2006, Pattern Recognit. Lett..